K. Obermayer

Klaus Obermayer, Thore Graepel, Sambu Seo, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Learning Preference Relations for Information Retrieval

K. Obermayer, T. Graepel, R. Herbrich, 1998 .

Contrast Adaptation and Infomax in Visual Cortical Neurons

K. Obermayer, P. Adorján, C. Piepenbrock, 1999, Reviews in the neurosciences.

A Stochastic Self-Organizing Map for Proximity Data

Klaus Obermayer, Thore Graepel, K. Obermayer, 1999, Neural Computation.

PHASE TRANSITIONS IN STOCHASTIC SELF-ORGANIZING MAPS

K. Obermayer, T. Graepel, M. Burger, 1997 .

Principal Component Analysis and Blind Separation of Sources for Optical Imaging of Intrinsic Signals

K. Obermayer, F. Sengpiel, T. Bonhoeffer, 2000, NeuroImage.

Risk-Sensitive Reinforcement Learning

Klaus Obermayer, Tobias Sommer, Yun Shen, 2013, Neural Computation.

Regularized Sparse Kernel Slow Feature Analysis

Klaus Obermayer, Wendelin Böhmer, Hannes Nickisch, 2011, ECML/PKDD.

Towards Community Detection in k-Partite k-Uniform Hypergraphs

K. Obermayer, N. Neubauer, 2009 .

Nonlinear Feature Selection with the Potential Support Vector Machine

Klaus Obermayer, Sepp Hochreiter, S. Hochreiter, 2006, Feature Extraction.

Classification, Regression, and Feature Selection on Matrix Data

S. Hochreiter, K. Obermayer, 2004 .

Altered behavioral and neural responsiveness to counterfactual gains in the elderly

Michael J. Tobia, K. Obermayer, J. Gläscher, 2016, Cognitive, affective & behavioral neuroscience.

Statistical Physics of Clustering Algorithms

K. Obermayer, M. Burger, 1998 .

On the operating point of cortical computation

Klaus Obermayer, Marcel Stimberg, Klaus Wimmer, 2010 .

The operating regime of local computations in primary visual cortex.

Klaus Obermayer, David C Lyon, Lars Schwabe, 2009, Cerebral cortex.

Rapid adaptation to internal states as a coding strategy in visual cortex?

Klaus Obermayer, Lars Schwabe, Gregor Wenning, 2002, Neuroreport.

Dorsolateral prefrontal cortex contributes to the impaired behavioral adaptation in alcohol dependence☆

K. Obermayer, L. Deserno, A. Heinz, 2017, NeuroImage: Clinical.

A computational study on synaptic and extrasynaptic effects of astrocyte glutamate uptake on orientation tuning in V1

M. Sur, K. Obermayer, Konstantin Mergenthaler, 2017, 1701.08663.

Orientation Selective Cells Emerge in a Sparsely CodingBoltzmann

K. Obermayer, MachineCornelius Weber, 1999 .

Model-Free Temporal-Difference Learning and Dopamine in Alcohol Dependence: Examining Concepts From Theory and Animals in Human Imaging.

K. Obermayer, Q. Huys, L. Deserno, 2016, Biological psychiatry. Cognitive neuroscience and neuroimaging.

The effect of novelty on reinforcement learning.

K. Obermayer, Wendelin Böhmer, R. Lorenz, 2013, Progress in brain research.

Gene Selection on Micro Array Data through Support Vector Machines

S. Hochreiter, K. Obermayer, 2013 .

Classification, Regression, and Feature Selection

Klaus Obermayer, Sepp Hochreiter, Revised December, 2004 .

Using unlabeled data for supervised learning

Klaus Obermayer, Thore Graepel, Ralf Herbrich, 1999 .

How adaptation currents change threshold, gain, and variability of neuronal spiking.

Klaus Obermayer, Josef Ladenbauer, Moritz Augustin, 2013, Journal of neurophysiology.

Perceptual Representations for Classification of Everyday Sounds

Klaus Obermayer, Kamil Adiloglu, P. Purwins, 2007 .

Optimal noise-aided signal transmission through populations of neurons.

K. Obermayer, G. Wenning, T. Hoch, 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

Biology and Theory of Early Stages of Vision in Mammals

K. Obermayer, M. Stetter, 2007 .

Biology and Theory of Early Vision in Mammals

K. Obermayer, M. Stetter, 2000 .

Interaction of Instrumental and Goal-Directed Learning Modulates Prediction Error Representations in the Ventral Striatum

K. Obermayer, J. Gläscher, Wendelin Böhmer, 2016, The Journal of Neuroscience.

Predicting the future relapse of alcohol‐dependent patients from structural and functional brain images

K. Obermayer, T. Wüstenberg, A. Heinz, 2015, Addiction biology.

Potential Support Vector Machines for Dyadic Data

S. Hochreiter, K. Obermayer, 2013 .

Sphered Support Vector Machine

S. Hochreiter, K. Obermayer, J. Mohr, 2012 .

Sequence Classification For Protein Analysis

S. Hochreiter, K. Obermayer, 2013 .

Modulation of the amplitude of γ‐band activity by stimulus phase enhances signal encoding

K. Obermayer, M. Volgushev, A. Malyshev, 2011, The European journal of neuroscience.

Optimal kernels for unsupervised learning

S. Hochreiter, K. Obermayer, S. Hochreiter, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

PR ] 9 A ug 2 01 8 Conjugate Duality on Wasserstein Spaces with Applications in Partially Observable Markov Decision Processes

K. Obermayer, Yun Shen, W. Stannat, 2018 .

A Frank mixture copula family for modeling higher-order correlations of neural spike counts

K. Obermayer, A. Onken, 2009 .

Extending integrate-and-fire model neurons to account for input filtering and the effects of weak electric fields mediated by the dendrite

K. Obermayer, J. Ladenbauer, F. Aspart, 2016 .

Computing Auditory Perception from the Icmc Workshop 'cognition and Perception Issues in Computer Music'

K. Obermayer, B. Blankertz, H. Purwins, 2000 .

Patterned Brain Stimulation, What a Framework with Rhythmic and Noisy Components Might Tell Us about Recovery Maximization

K. Obermayer, S. Brandt, M. Scholz, 2013, Front. Hum. Neurosci..

Gene Selection for Microarray Data

Klaus Obermayer, Sepp Hochreiter, S. Hochreiter, 2004 .

A New Algorithm for the Interrogation of 3D Holographic Particle Tracking Velocimetry Data Based on Deterministic Annealing and EM-Optimization

K. Obermayer, R. Krepki, 2000 .

Fast phytoplankton classification from fluorescence spectra: comparison between PSVM and SOM

I. F. Aymerich, K. Obermayer, A. Soria-Frisch, 2009, OCEANS 2009-EUROPE.

Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, NIPS 2004, December 13-18, 2004, Vancouver, British Columbia, Canada]

Sebastian Thrun, Klaus Obermayer, Suzanna Becker, 2004, NIPS.

Risk-averse reinforcement learning for algorithmic trading

Klaus Obermayer, Chang Yan, Yun Shen, 2014, 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).

A Unified Framework for Risk-sensitive Markov Decision Processes with Finite State and Action Spaces

Klaus Obermayer, Wilhelm Stannat, Yun Shen, 2011, ArXiv.

A simulated extracellular recording environment for the evaluation of automated electrode positioning systems and spike sorting algorithms

Klaus Obermayer, Felix Franke, K. Obermayer, 2010 .

Risk profiles for heavy drinking in adolescence: differential effects of gender

K. Obermayer, C. Büchel, H. Flor, 2018, Addiction biology.

Extending integrate-and fire model neurons to account for the effects of weak electric fields in the presence of dendrites

K. Obermayer, J. Ladenbauer, F. Aspart, 2015, BMC Neuroscience.

State-dependent effects of electrical stimulation on populations of excitatory and inhibitory neurons

K. Obermayer, Caglar Cakan, 2019 .

Real-Time Statistical Learning for Oculomotor Control and Visuomotor Coordination

Sethu Vijayakumar, Stefan Schaal, K. Obermayer, 2002, NIPS 2002.

Cross-Frequency Slow Oscillation–Spindle Coupling in a Biophysically Realistic Thalamocortical Neural Mass Model

K. Obermayer, Caglar Cakan, N. Jajcay, 2022, Frontiers in Computational Neuroscience.

Active Data Selection for Fuzzy Topographic Mapping of Proximities

Martina Hasenjäger, Helge Ritter, Klaus Obermayer, 1999 .

Hyperincident connected components of tagging networks

K. Obermayer, N. Neubauer, 2009, LINK.

Proceedings of the 15th International Conference on Neural Information Processing Systems

Sebastian Thrun, Klaus Obermayer, Suzanna Becker, 2002 .

Learning from invariants predicts upcoming behavioral choice from spiking activity in monkey V1

Ariana R. Andrei, K. Obermayer, Valentin Dragoi, 2022, bioRxiv.

The optimal unbiased value estimator and its relation to LSTD, TD and MC

K. Obermayer, S. Grünewälder, 2009, Machine Learning.

State Extraction by Dimensionality Reduction

K. Obermayer, Wendelin Böhmer, 2004 .

Synchronization Through Uncorrelated Noise in Excitatory-Inhibitory Networks

K. Obermayer, Christoph Metzner, Lucas Rebscher, 2021, Frontiers in Computational Neuroscience.

A Fenchel-Moreau-Rockafellar type theorem on the Kantorovich-Wasserstein space with applications in partially observable Markov decision processes

K. Obermayer, Yun Shen, W. Stannat, 2016, Journal of Mathematical Analysis and Applications.

Risk-Sensitive Partially Observable Markov Decision Processes as Fully Observable Multivariate Utility Optimization problems

K. Obermayer, Vaios Laschos, Arsham Afsardeir, 2018, 1808.04478.

Representations and Predictors for Everyday Sounds

Klaus Obermayer, Kamil Adiloglu, P. Purwins, 2008 .

NAPC: A Neural Algorithm for Automated Passenger Counting in Public Transport on a Privacy-Friendly Dataset

K. Obermayer, Sambu Seo, R. Seidel, 2022, IEEE Open Journal of Intelligent Transportation Systems.

Distance Measures in Query Space: How Strongly to Use Feedback From Past Queries

Klaus Obermayer, Sahin Albayrak, Christian Scheel, 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'07).

Controlling statistical moments of stochastic dynamical networks.

K. Obermayer, J. Ladenbauer, D. Bielievtsov, 2015, Physical review. E.

Risk-Sensitive Markov Control Processes

K. Obermayer, Yun Shen, W. Stannat, 2011, SIAM J. Control. Optim..

On Average Risk-sensitive Markov Control Processes

K. Obermayer, Yun Shen, W. Stannat, 2014, 1403.3321.

Transfer Learning for Segmentation Problems: Choose the Right Encoder and Skip the Decoder

K. Obermayer, M. Lenga, Thomas Goerttler, 2022, ArXiv.

Automatic spike sorting evaluation: A website based community approach

Klaus Obermayer, Gaute T. Einevoll, Thomas Wachtler, 2014 .

Nonlinear optimal control of a mean-field model of neural population dynamics

K. Obermayer, L. Salfenmoser, 2022, Frontiers in Computational Neuroscience.

Effects of neuronal adaptation currents on network-based spike rate oscillations

K. Obermayer, J. Ladenbauer, Moritz Augustin, 2013, BMC Neuroscience.

Learning Rules: Overview

K. Obermayer, 2019, Encyclopedia of Computational Neuroscience.

Changes in V1 orientation tuning when blocking astrocytic glutamate transporters: models for extra- and intrasynaptic mechanisms

M. Sur, K. Obermayer, Konstantin Mergenthaler, 2013, BMC Neuroscience.

Deliverable D 4 . 2 Specification of feedback loops and implementation progress

K. Obermayer, J. Blauert, P. Danès, 2015 .

5 Toroidal Models in Tonal Theory and Pitch- Class Analysis

Klaus Obermayer, Benjamin Blankertz, Hendrik Purwins, 2007 .

Toroidal models of inter-key relations in tonal music

Klaus Obermayer, Benjamin Blankertz, P. Purwins, 1999 .

Correspondence Analysis for Visualizing Interplay of Pitch Class, Key, and Composer

Klaus Obermayer, Benjamin Blankertz, Thore Graepel, 2003 .

A Model for the Development of the Spatial Structure of Retinotopic Maps and Orientation Columns

Klaus Obermayer, Helge Ritter, Helge Ritter, 1992 .

Why it is hard to generate orientation and ocular dominance with linear correlation based learning models

Klaus Obermayer, Helge Ritter, Christian Piepenbrock, 1995, NIPS 1995.

Spike sorting of synchronous spikes from local neuron ensembles.

Henrik Alle, Klaus Obermayer, Philipp Meier, 2015, Journal of neurophysiology.

Erratum to: Bayes optimal template matching for spike sorting – combining fisher discriminant analysis with optimal filtering

Klaus Obermayer, Rodrigo Quian Quiroga, Andreas Hierlemann, 2015, Journal of Computational Neuroscience.

Bayes optimal template matching for spike sorting – combining fisher discriminant analysis with optimal filtering

K. Obermayer, R. Quiroga, F. Franke, 2015, Journal of Computational Neuroscience.

Structured models from structured data: emergence of modular information processing within one sheet of neurons

Cornelius Weber, Klaus Obermayer, K. Obermayer, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

New methods for the computer-assisted 3-D reconstruction of neurons from confocal image stacks

Michael Scholz, Klaus Obermayer, Jan Felix Evers, 2004, NeuroImage.

Neural pattern formation via a competitive Hebbian mechanism

K. Obermayer, T. Sejnowski, K. Obermayer, 1995, Behavioural Brain Research.

Self-organizing maps and adaptive filters

Klaus Schulten, Helge Ritter, Klaus Obermayer, 1991 .

Large-scale simulations of self-organizing neural networks on parallel computers: application to biological modelling

Helge J. Ritter, Klaus Schulten, Klaus Obermayer, 1990, Parallel Comput..

Weak electric fields promote resonance in neuronal spiking activity: Analytical results from two-compartment cell and network models

Klaus Obermayer, Josef Ladenbauer, K. Obermayer, 2018, bioRxiv.

Differential polarization of cortical pyramidal neuron dendrites through weak extracellular fields

Klaus Obermayer, Michiel W. H. Remme, Florian Aspart, 2017, bioRxiv.

Extending Integrate-and-Fire Model Neurons to Account for the Effects of Weak Electric Fields and Input Filtering Mediated by the Dendrite

Klaus Obermayer, Josef Ladenbauer, Florian Aspart, 2016, PLoS Comput. Biol..

Emergence of Modularity within One Sheet of Neurons: A Model Comparison

Cornelius Weber, Klaus Obermayer, K. Obermayer, 2001, Emergent Neural Computational Architectures Based on Neuroscience.

Dynamics of Orientation Tuning in Cat V1 Neurons Depend on Location Within Layers and Orientation Maps

Klaus Obermayer, Mriganka Sur, Robert Martin, 2007, Front. Neurosci..

Support Vector Machines for Dyadic Data

Klaus Obermayer, Sepp Hochreiter, S. Hochreiter, 2006, Neural Computation.

neurolib: a simulation framework for whole-brain neural mass modeling

K. Obermayer, Caglar Cakan, N. Jajcay, 2021, bioRxiv.

Spatiotemporal Patterns of Adaptation-Induced Slow Oscillations in a Whole-Brain Model of Slow-Wave Sleep

K. Obermayer, A. Flöel, Caglar Cakan, 2020, Frontiers in Computational Neuroscience.

A deep sleep model of the human brain: how slow waves emerge due to adaptation and are guided by the connectome

K. Obermayer, A. Flöel, Caglar Cakan, 2020 .

A New Incremental Pairwise Clustering Algorithm

Klaus Obermayer, Sambu Seo, Johannes Mohr, 2009, 2009 International Conference on Machine Learning and Applications.

Regression Models for Ordinal Data: A Machine Learning Approach

Klaus Obermayer, Thore Graepel, Ralf Herbrich, 1999 .

Computing auditory perception

Klaus Obermayer, Benjamin Blankertz, Hendrik Purwins, 2000, Organised Sound.

Tripartite community structure in social bookmarking data

Nicolas Neubauer, Klaus Obermayer, K. Obermayer, 2011, New Rev. Hypermedia Multim..

Closing the loop of sound evaluation and design

Davide Rocchesso, Klaus Obermayer, Patrick Susini, 2006 .

25th Annual Computational Neuroscience Meeting: CNS-2016

Morten L. Kringelbach, Majid Nili Ahmadabadi, Anders M. Dale, 2016, BMC Neuroscience.

An Online Data Visualization Feedback Protocol for Motor Imagery-Based BCI Training

K. Obermayer, Xinzhou Xie, Songyun Xie, 2021, Frontiers in Human Neuroscience.

Joining Sound Event Detection and Localization Through Spatial Segregation

Dorothea Kolossa, Klaus Obermayer, Christopher Schymura, 2019, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

Automated Tumors Extraction and Visualization in Nasal and Paranasal Sinuses

K. Obermayer, M. Scholz, A. Hess, 2004 .

A new summarization method for affymetrix probe level data

Klaus Obermayer, Sepp Hochreiter, Djork-Arné Clevert, 2006, Bioinform..

Towards optimization of oscillatory stimulation during sleep

K. Obermayer, D. Antonenko, A. Flöel, 2021, bioRxiv.

Structural Differences Between Healthy Subjects and Patients With Schizophrenia or Schizoaffective Disorder: A Graph and Control Theoretical Perspective

K. Obermayer, S. Fromm, F. Kamp, 2021, Frontiers in Psychiatry.

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3

Silvestro Micera, Johannes Schemmel, Szabolcs Káli, 2017, BMC Neuroscience.

Extending Bron Kerbosch for Solving the Maximum Weight Clique Problem pdf

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2011, ArXiv.

A Necessary and Sufficient Condition for Graph Matching Being Equivalent to the Maximum Weight Clique Problem pdf

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2009, ArXiv.

Blind signal separation from optical imaging recordings with extended spatial decorrelation

Klaus Obermayer, John E. W. Mayhew, Martin Stetter, 2000, IEEE Transactions on Biomedical Engineering.

Putative strategies of scene segmentation in monkey visual cortex

GARY BLASDEL, KLAUS OBERMAYER, K. Obermayer, 1994, Neural Networks.

A new point-based warping method for enhanced and simplified analysis of functional brain image data

Michael Scholz, Klaus Obermayer, Andreas Hess, 2003, NeuroImage.

State and Religion in the Federal Republic of Germany

K. Obermayer, 1975 .

Religious schools and religious freedom: proposals for reform of the german public school system

K. Obermayer, 1968 .

Adaptation and Selective Information Transmission in the Cricket Auditory Neuron AN2

Klaus Obermayer, R. Matthias Hennig, Klaus Wimmer, 2008, PLoS Comput. Biol..

Modeling the adaptive visual system: a survey of principled approaches

Klaus Obermayer, Lars Schwabe, K. Obermayer, 2003, Neural Networks.

Rapid adaptation and efficient coding.

Klaus Obermayer, Lars Schwabe, K. Obermayer, 2002, Bio Systems.

Development of feedforward receptive field structure of a simple cell and its contribution to the orientation selectivity: a modeling study

Klaus Obermayer, Basabi Bhaumik, Akhil R. Garg, 2005, Int. J. Neural Syst..

A systems medicine research approach for studying alcohol addiction

Klaus Obermayer, Daniel Durstewitz, Henrik Walter, 2013, Addiction biology.

Objects guide human gaze behavior in dynamic real-world scenes

K. Obermayer, M. Rolfs, O. Hellwich, 2023, bioRxiv.

The effect of intracortical competition on the formation of topographic maps in models of Hebbian learning

Klaus Obermayer, Christian Piepenbrock, K. Obermayer, 2000, Biological Cybernetics.

Interrelations between delta waves, spindles and slow oscillations in human NREM sleep and their functional role in memory

K. Obermayer, D. Antonenko, A. Flöel, 2021, bioRxiv.

Cross-Frequency Slow Oscillation–Spindle Coupling in a Biophysically Realistic Thalamocortical Neural Mass Model

K. Obermayer, Caglar Cakan, N. Jajcay, 2021, bioRxiv.

Low-dimensional spike rate models derived from networks of adaptive integrate-and-fire neurons: Comparison and implementation

Klaus Obermayer, Josef Ladenbauer, Moritz Augustin, 2016, PLoS Comput. Biol..

A COMPARISON OF MODELS OFVISUAL CORTICAL

K. Obermayer, M. Erwin, Klaus SchultenBeckman, 1993 .

A Comparison between a Neural Network Model for the Formation of Brain Maps and Experimental Data

Klaus Schulten, Klaus Obermayer, Gary G. Blasdel, 1991, NIPS.

An Analysis of Orientation and Ocular Dominance Patterns in the Visual Cortex of Cats and Ferrets

Tobias Bonhoeffer, Mark Hübener, Martin Stetter, 2000, Neural Computation.

Singularities in Primate Orientation Maps

Klaus Obermayer, Gary G. Blasdel, K. Obermayer, 1997, Neural Computation.

The NIGENS General Sound Events Database pdf

Klaus Obermayer, Jalil Taghia, Ivo Trowitzsch, 2019, ArXiv.

From in silico astrocyte cell models to neuron-astrocyte network models: A review

Klaus Obermayer, Hugues Berry, Kerstin Lenk, 2018, Brain Research Bulletin.

Spatial separation of two different pathways accounting for the generation of calcium signals in astrocytes

Klaus Obermayer, Konstantin Mergenthaler, Franziska Oschmann, 2017, PLoS Comput. Biol..

Contextual effects by short range connections in a mean-field model of V1

Klaus Obermayer, Hauke Bartsch, Martin Stetter, 2001, Neurocomputing.

On the Influence of Threshold Variability in a Mean-Field Model of the Visual Cortex

Martin Stetter, Klaus Obermayer, Hauke Bartsch, 2001, Emergent Neural Computational Architectures Based on Neuroscience.

The influence of threshold variability on the response of visual cortical neurons

Klaus Obermayer, Hauke Bartsch, Martin Stetter, 2000, Neurocomputing.

Attention driven memory

K. Obermayer, S. Grünewälder, 2005 .

Systems Neurobiology of the Dysfunctional Brain: Schizophrenia

K. Obermayer, A. Heinz, J. Gallinat, 2007 .

Multivariate Utility Optimization with an Application to Risk-Sensitive Partially Observable Markov Decision Processes

Robert Seidel, Klaus Obermayer, Vaios Laschos, 2018 .

Risk Sensitive Multiple Goal Stochastic Optimization, with application to Risk Sensitive Partially Observed Markov Decision Processes

Klaus Obermayer, Robert Seidel, Vaios Laschos, 2018 .

A Conjugate Approach to Partially Observable Markov Decision Processes on Borel Spaces

K. Obermayer, Yun Shen, W. Stannat, 2016 .

Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations

Klaus Obermayer, Wendelin Böhmer, Martin A. Riedmiller, 2015, KI - Künstliche Intelligenz.

Coulomb Classifiers: Generalizing Support Vector Machines via an Analogy to Electrostatic Systems

Klaus Obermayer, Michael C. Mozer, Sepp Hochreiter, 2002, NIPS.

Gaussian Process Regression: Active Data Selection and Test Point

Klaus Obermayer, Thore Graepel, Sambu Seo, 2000 .

Models of Acetylcholine and Dopamine Signals Differentially Improve Neural Representations

Jörg Lücke, Klaus Obermayer, Raphaël Holca-Lamarre, 2017, Front. Comput. Neurosci..

Detection of pulses in a colored noise setting.

Klaus Obermayer, Gregor Wenning, Thomas Hoch, 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

Activity Driven Adaptive Stochastic Resonance

Klaus Obermayer, Gregor Wenning, K. Obermayer, 2001, NIPS.

How adaptation shapes spike rate oscillations in recurrent neuronal networks

Klaus Obermayer, Josef Ladenbauer, Moritz Augustin, 2012, Front. Comput. Neurosci..

Self-organizing maps: ordering, convergence properties and energy functions

Klaus Schulten, Klaus Obermayer, E. Erwin, 1992, Biological Cybernetics.

A Maximum Entropy Test for Evaluating Higher-Order Correlations in Spike Counts

Klaus Obermayer, Arno Onken, Valentin Dragoi, 2012, PLoS Comput. Biol..

A model comparison of COMT effects on central processing of affective stimuli

Andreas Heinz, Jana Wrase, Michael N. Smolka, 2009, NeuroImage.

Map location affects center-surround modulation in a network model of V1

Klaus Obermayer, Marcel Stimberg, K. Obermayer, 2009, BMC Neuroscience.

Self-organizing maps: Generalizations and new optimization techniques

Klaus Obermayer, Thore Graepel, Matthias Burger, 1998, Neurocomputing.

Afferent specificity, feature specific connectivity influence orientation selectivity: A computational study in mouse primary visual cortex

Klaus Obermayer, Dipanjan Roy, Mriganka Sur, 2013, 1301.0996.

Analysis of Calcium Imaging Signals from the Honeybee Brain by Nonlinear Models

K. Obermayer, M. Stetter, H. Greve, 2001, NeuroImage.

Solving large systems of differential equations in parallel using covers and skeletons

Klaus Obermayer, Peter Pepper, Mario Südholt, 1997, Algorithmic Languages and Calculi.

Neural Networks in Economics

Thore Graepel, Ralf Herbrich, Peter Bollmann-Sdorra, 1999 .

A Hippocampal Signature of Perceptual Learning in Object Recognition

Klaus Obermayer, John-Dylan Haynes, Philipp Sterzer, 2015, Journal of Cognitive Neuroscience.

A computer vision system for rapid search inspired by surface-based attention mechanisms from human perception

Johannes Mohr, Klaus Obermayer, Jong-Han Park, 2014, Neural Networks.

Quadratic optimization for simultaneous matrix diagonalization

Klaus Obermayer, Roland Vollgraf, K. Obermayer, 2006, IEEE Transactions on Signal Processing.

Intrinsic Control Mechanisms of Neuronal Network Dynamics

Klaus Obermayer, Josef Ladenbauer, Moritz Augustin, 2016 .

Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons

Klaus Obermayer, Josef Ladenbauer, LieJune Shiau, 2012, PLoS Comput. Biol..

Reading-out task variables as a low-dimensional reconstruction of neural spike trains in single trials

Klaus Obermayer, Valentin Dragoi, Veronika Koren, 2019, bioRxiv.

Integrator or Coincidence Detector: A Novel Measure Based on the Discrete Reverse Correlation to Determine a Neuron’s Operational Mode

Klaus Obermayer, Chris Christodoulou, Jacob Kanev, 2016, Neural Computation.

Variable Discharge Pattern and Contrast Invariant Orientation Tuning of a Simple Cell: A Modeling Study

K. Obermayer, A. Garg, B. Bhaumik, 2005 .

The Balance Between Excitation and Inhibition Not Only Leads to Variable Discharge of Cortical Neurons but Also to Contrast Invariant Orientation Tuning

Klaus Obermayer, Basabi Bhaumik, Akhil R. Garg, 2004, ICONIP.

A paradigmatic approach to extract the melodic structure of a musical piece

Klaus Obermayer, Kamil Adiloglu, Thomas Noll, 2006 .

Biophysically grounded mean-field models of neural populations under electrical stimulation

Klaus Obermayer, Caglar Cakan, K. Obermayer, 2019, PLoS Comput. Biol..

Neural Networks in Economics: Background, Applications and New Developments

Thore Graepel, Ralf Herbrich, Peter Bollmann-Sdorra, 1998 .

Self-organizing maps: stationary states, metastability and convergence rate

Klaus Schulten, Klaus Obermayer, E. Erwin, 1992, Biological Cybernetics.

Correction methods for three-dimensional reconstructions from confocal images: I. tissue shrinking and axial scaling

K. Obermayer, Dirk Bucher, H. Pflüger, 2000, Journal of Neuroscience Methods.

A mean-field model for orientation tuning, contrast saturation, and contextual effects in the primary visual cortex

Klaus Obermayer, Hauke Bartsch, Martin Stetter, 2000, Biological Cybernetics.

Altered behavioral and neural responsiveness to counterfactual gains in the elderly

Michael J. Tobia, K. Obermayer, J. Gläscher, 2016, Cognitive, Affective, & Behavioral Neuroscience.

Visualization of synaptic markers in the optic neuropils of Drosophila using a new constrained deconvolution method

I A Meinertzhagen, K. Obermayer, P. Hiesinger, 2001, The Journal of comparative neurology.

Applications of optimal nonlinear control to a whole-brain network of FitzHugh-Nagumo oscillators.

K. Obermayer, Caglar Cakan, Nicolas Roth, 2021, Physical review. E.

Applications of nonlinear control to a whole-brain network of FitzHugh-Nagumo oscillators pdf

Klaus Obermayer, Caglar Cakan, Teresa Chouzouris, 2021, ArXiv.

Neural systems for choice and valuation with counterfactual learning signals

Christian Büchel, Klaus Obermayer, Wendelin Böhmer, 2014, NeuroImage.

Extending integrate-and fire model neurons to account for the effects of weak electric fields in the presence of dendrites

K. Obermayer, J. Ladenbauer, F. Aspart, 2015, BMC Neuroscience.

Erratum: Cortical reorganization consistent with spike timing-but not correlation-dependent plasticity (Nature Neuroscience (2007) 10, (887-895))

Klaus Obermayer, Michael B. Calford, Wioletta J. Waleszczyk, 2007 .

Performance of 3D landmark detection methods for point-based warping in autoradiographic brain imaging

Michael Scholz, Klaus Obermayer, Andreas Hess, 2002, Proceedings Fifth IEEE Southwest Symposium on Image Analysis and Interpretation.

Point-based warping with optimized weighting factors of displacement vectors

Michael Scholz, Klaus Obermayer, Andreas Hess, 2000, Medical Imaging: Image Processing.

Warping with optimized weighting factors of displacement vectors-a new method to reduce inter-individual variations in brain imaging

Michael Scholz, Klaus Obermayer, Andreas Hess, 2000, 4th IEEE Southwest Symposium on Image Analysis and Interpretation.

Neurotransmitter Systems in Alcohol Dependence

K. Obermayer, A. Heinz, J. Wrase, 2009, Pharmacopsychiatry.

Analyzing Short-Term Noise Dependencies of Spike-Counts in Macaque Prefrontal Cortex Using Copulas and the Flashlight Transformation

Klaus Obermayer, Steffen Grünewälder, Arno Onken, 2009, PLoS Comput. Biol..

A new method for tracking modulations in tonal music in audio data format

Klaus Obermayer, Benjamin Blankertz, Hendrik Purwins, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Adaptation at synaptic connections to layer 2/3 pyramidal cells in rat visual cortex.

Klaus Obermayer, Maxim Volgushev, Marina Chistiakova, 2005, Journal of neurophysiology.

The effect of background noise on the precision of pulse packet propagation in feed-forward networks

Klaus Obermayer, Marcel Stimberg, Thomas Hoch, 2007, Neurocomputing.

The effect of correlations in the background activity on the information transmission properties of neural populations

Klaus Obermayer, Gregor Wenning, Thomas Hoch, 2005, Neurocomputing.

Structure Spaces

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2009, J. Mach. Learn. Res..

Dynamics of the Hippocampus: Multiple Strategies

Péter Érdi, Klaus Obermayer, Ádám Kepecs, 1998, ICONIP.

Tag spam creates large non-giant connected components

Klaus Obermayer, Robert Wetzker, Nicolas Neubauer, 2009, AIRWeb '09.

An Unsupervised and Drift-Adaptive Spike Detection Algorithm Based on Hybrid Blind Beamforming

Klaus Obermayer, Michal Natora, K. Obermayer, 2011, EURASIP J. Adv. Signal Process..

Soft Learning Vector Quantization

Klaus Obermayer, Sambu Seo, K. Obermayer, 2003, Neural Computation.

Generalized Learning Graph Quantization

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2011, GbRPR.

Patterned Brain Stimulation, What a Framework with Rhythmic and Noisy Components Might Tell Us about Recovery Maximization

K. Obermayer, S. Brandt, M. Scholz, 2013, Frontiers in Human Neuroscience.

Robust Detection of Environmental Sounds in Binaural Auditory Scenes

Klaus Obermayer, Ivo Trowitzsch, Johannes Mohr, 2017, IEEE/ACM Transactions on Audio, Speech, and Language Processing.

A new clustering approach for partitioning directional data

K. Obermayer, C. Klose, S. Seo, 2005 .

Adaptation controls synchrony and cluster states of coupled threshold-model neurons.

Josef Ladenbauer, Eckehard Schöll, Judith Lehnert, 2013, Physical review. E, Statistical, nonlinear, and soft matter physics.

pypet: A Python Toolkit for Data Management of Parameter Explorations

Klaus Obermayer, Robert Meyer, K. Obermayer, 2016, Front. Neuroinform..

Self-organizing maps and clustering methods for matrix data

Klaus Obermayer, Sambu Seo, K. Obermayer, 2004, Neural Networks.

Sequence classificatio n for protein analysis

Klaus Obermayer, Sepp Hochreiter, S. Hochreiter, 2005 .

Empirically identifying and computationally modelling the brain-behaviour relationship for human scene categorization

Tim C Kietzmann, K. Obermayer, R. Cichy, 2023, bioRxiv.

Optimality of LSTD and its Relation to MC

Klaus Obermayer, Steffen Grünewälder, Sepp Hochreiter, 2007, 2007 International Joint Conference on Neural Networks.

A unified framework for risk-sensitive Markov control processes

Klaus Obermayer, Wilhelm Stannat, Yun Shen, 2014, 53rd IEEE Conference on Decision and Control.

Non-Deterministic Policy Improvement Stabilizes Approximated Reinforcement Learning pdf

Klaus Obermayer, Wendelin Böhmer, Rong Guo, 2016, ArXiv.

A spatial selective visual attention pattern recognition method based on joint short SSVEP

Klaus Obermayer, Petra Ritter, Songyun Xie, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Synergistic effects of the dopaminergic and glutamatergic system on hippocampal volume in alcohol-dependent patients

K. Obermayer, H. Breiter, N. Makris, 2008, Biological Psychology.

Simulation of scanning laser techniques for optical imaging of blood-related intrinsic signals.

K. Obermayer, M. Stetter, M Stetter, 1999, Journal of the Optical Society of America. A, Optics, image science, and vision.

The Influence of Mexican Hat Recurrent Connectivity on Noise Correlations and Stimulus Encoding

Klaus Obermayer, Robert Meyer, Josef Ladenbauer, 2017, Front. Comput. Neurosci..

Effects of lateral competition in the primary visual cortex on the development of topographic projections and ocular dominance maps

Klaus Obermayer, Christian Piepenbrock, K. Obermayer, 1999, Neurocomputing.

Bayesian Transduction

Klaus Obermayer, Thore Graepel, Ralf Herbrich, 1999, NIPS.

Modeling spike-count dependence structures with multivariate Poisson distributions

K. Obermayer, A. Onken, 2008, BMC Neuroscience.

Spyke Viewer: a flexible and extensible platform for electrophysiological data analysis

Klaus Obermayer, Robert Pröpper, K. Obermayer, 2013, Front. Neuroinform..

Approximate Inference for Time-Varying Interactions and Macroscopic Dynamics of Neural Populations

Klaus Obermayer, Hideaki Shimazaki, Christian Donner, 2016, PLoS Comput. Biol..

Consistent Estimator of Median and Mean Graph

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2010, 2010 20th International Conference on Pattern Recognition.

Development and Spatial Structure of Cortical Feature Maps: A Model Study

Helge J. Ritter, Klaus Schulten, Klaus Obermayer, 1990, NIPS.

Exploring the Similarity of Representations in Model-Agnostic Meta-Learning pdf

Klaus Obermayer, Thomas Goerttler, K. Obermayer, 2021, ArXiv.

The operating regime of local computations in primary visual cortex.

M. Sur, K. Obermayer, D. C. Lyon, 2009, Cerebral cortex.

Automated Microarray Classification Based on P-SVM Gene Selection

Klaus Obermayer, Sambu Seo, Johannes Mohr, 2008, 2008 Seventh International Conference on Machine Learning and Applications.

Target Selection: A New Learning Paradigm and Its Application to Genetic Association Studies

Klaus Obermayer, Andreas Heinz, Sambu Seo, 2008, 2008 Seventh International Conference on Machine Learning and Applications.

P-SVM Variable Selection for Discovering Dependencies Between Genetic and Brain Imaging Data

Klaus Obermayer, Andreas Heinz, Jana Wrase, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Optimal gradient-based learning using importance weights

S. Hochreiter, K. Obermayer, S. Hochreiter, 2005, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Further Challenges and the Road Ahead

Dorothea Kolossa, Klaus Obermayer, Jens Blauert, 2013 .

An SMO Algorithm for the Potential Support Vector Machine

Klaus Obermayer, Sepp Hochreiter, Tilman Knebel, 2008, Neural Computation.

Feature Selection and Classification on Matrix Data: From Large Margins to Small Covering Numbers

Klaus Obermayer, Sepp Hochreiter, S. Hochreiter, 2002, NIPS.

The intersection between the representation of the stimuli and the choice by neural ensembles in the primary visual cortex of the macaque.

Ming Hu, Valentin Dragoi, Veronika Koren, 2020 .

Choice can be predicted from populations of bursting neurons in superficial layers of monkey V1

Ming Hu, Valentin Dragoi, Veronika Koren, 2020, SSRN Electronic Journal.

Contrast Adaptation in Simple Cells by Changing the Transmitter Release Probability

Klaus Obermayer, Péter Adorján, K. Obermayer, 1998, NIPS.

Orientation plasticity and the tilt aftereffect in network models of V1

Klaus Obermayer, Klaus Wimmer, K. Obermayer, 2009, BMC Neuroscience.

Objects guide human gaze behavior in dynamic real-world scenes

K. Obermayer, M. Rolfs, O. Hellwich, 2023, bioRxiv.

Recurrent Cortical Competition: Strengthen or Weaken?

Klaus Obermayer, Lars Schwabe, Christian Piepenbrock, 1999, NIPS.

Empirically Identifying and Computationally Modeling the Brain–Behavior Relationship for Human Scene Categorization

Tim C Kietzmann, K. Obermayer, R. Cichy, 2023, Journal of Cognitive Neuroscience.

Influence of Recurrent Excitation and Inhibition on Receptive Field Size and Contrast Sensitivity in Layer 4C of Macaque Striate Cortex

J. B. Levitt, K. Obermayer, J. Lund, 1998 .

Development of a Simple Cell Receptive Field Structure: A Model Based on Hetero-synaptic Interactions

Klaus Obermayer, Basabi Bhaumik, Akhil R. Garg, 2004, ICONIP.

Statistical-mechanical analysis of self-organization and pattern formation during the development of visual maps.

K. Obermayer, G. Blasdel, K. Schulten, 1992, Physical review. A, Atomic, molecular, and optical physics.

The effect of novelty on reinforcement learning.

K. Obermayer, Wendelin Böhmer, R. Lorenz, 2013, Progress in brain research.

Speeding up algorithms of SOM Family for Large and High Dimensional Databases

Roseli A. F. Romero, Klaus Obermayer, Ernesto Cuadros-Vargas, 2003 .

Sparse Optimization for Second Order Kernel Methods

Klaus Obermayer, Roland Vollgraf, K. Obermayer, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

From in silico astrocyte cell models to neuron-astrocyte network models: A review

K. Obermayer, Hugues Berry, Franziska Oschmann, 2018, Brain Research Bulletin.

Regression with Linear Factored Functions

K. Obermayer, Wendelin Böhmer, 2014, ECML/PKDD.

Brian2CUDA: Flexible and Efficient Simulation of Spiking Neural Network Models on GPUs

K. Obermayer, Henning Sprekeler, M. Stimberg, 2022, Frontiers in Neuroinformatics.

Optimal control of a Wilson-Cowan model of neural population dynamics.

K. Obermayer, L. Salfenmoser, 2023, Chaos.

Risk-averse reinforcement learning for algorithmic trading

K. Obermayer, Yun Shen, Ruihong Huang, 2013, 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr).

Multi Dimensional ICA to Separate Correlated Sources

Klaus Obermayer, Roland Vollgraf, K. Obermayer, 2001, NIPS.

Risk Sensitivity under Partially Observable Markov Decision Processes

Dirk Ostwald, Klaus Obermayer, Rong Guo, 2019, 2019 Conference on Cognitive Computational Neuroscience.

Automatic segmentation and skeletonization of neurons from confocal microscopy images based on the 3-D wavelet transform

K. Obermayer, A. Dima, Michael Scholz, 2002, IEEE Transactions on Image Processing.

Automatic three-dimensional graph construction of nerve cells from confocal microscopy scans

Anca Dima, Michael Scholz, Klaus Obermayer, 2003, J. Electronic Imaging.

Learning in Riemannian Orbifolds pdf

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2012, ArXiv.

Elkan's k-Means Algorithm for Graphs

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2010, MICAI.

Large Sample Statistics in the Domain of Graphs

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2010, SSPR/SPR.

Graph quantization

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2010, Comput. Vis. Image Underst..

Accelerating Competitive Learning Graph Quantization pdf

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2010, ArXiv.

Elkan's k-Means for Graphs pdf

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2009, ArXiv.

Algorithms for the Sample Mean of Graphs

Klaus Obermayer, Brijnesh J. Jain, K. Obermayer, 2009, CAIP.

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3

Vito Paolo Pastore, Alfred B. Yu, Kelvin S. Oie, 2017, BMC Neuroscience.

Factored Representations for Regression

Klaus Obermayer, Wendelin Böhmer, K. Obermayer, 2014, ArXiv.