G. Deco

发表

Redundancy reduction with information-preserving nonlinear maps

L. Parra, G. Deco, S. Miesbach, 1995 .

An Information-Theoretic Approach to Neural Computing

G. Deco, D. Obradovic, 1997, Perspectives in Neural Computing.

Linear feature extraction in networks with lateral connections

G. Deco, D. Obradovic, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Higher Order Statistical Decorrelation without Information Loss

Gustavo Deco, Wilfried Brauer, G. Deco, 1994, NIPS.

A hierarchical neural system with attentional top–down enhancement of the spatial resolution for object recognition

G. Deco, B. Schürmann, 2000, Vision Research.

Nonlinear higher-order statistical decorrelation by volume-conserving neural architectures

Gustavo Deco, Wilfried Brauer, G. Deco, 1995, Neural Networks.

Brain tumor classification based on EEG hidden dynamics

Gustavo Deco, Rosaria Silipo, Helmut Bartsch, 1999, Intell. Data Anal..

Exploring the intrinsic information loss in single-humped maps by refining multi-symbol partitions

G. Deco, C. Schittenkopf, 1996 .

Information Flow in Chaotic Symbolic Dynamics for Finite and Infinitesimal Resolution

G. Deco, B. Schürmann, C. Schittenkopf, 1997 .

Non-linear Feature Extraction by Redundancy Reduction in an Unsupervised Stochastic Neural Network

Lucas C. Parra, Gustavo Deco, L. Parra, 1997, Neural Networks.

A Neuro-Cognitive Visual System for Object Recognition Based on Testing of Interactive Attentional Top – down Hypotheses

G. Deco, B. Schürmann, 2000, Perception.

A unified model of spatial and object attention based on inter-cortical biased competition

Tai Sing Lee, Gustavo Deco, G. Deco, 2002, Neurocomputing.

Information Dynamics

G. Deco, B. Schürmann, 2001, Springer New York.

Detection of Primary Brain Tumor Present in EEG signal using Wavelet Transform and Neural Network

G. Deco, R. Silipo, H. Bartsch, 2013 .

Neural Coding: Higher-Order Temporal Patterns in the Neurostatistics of Cell Assemblies

Kathryn B. Laskey, Gustavo Deco, Mathew E. Diamond, 2000, Neural Computation.

Top-down selective visual attention: A neurodynamical approach

G. Deco, J. Zihl, 2001 .

Independent Component Analysis: General Formulation and Linear Case

G. Deco, D. Obradovic, 1996 .

Detecting event-related time-dependent directional couplings

Ralph G. Andrzejak, Anders Ledberg, G. Deco, 2006 .

Identification of deterministic chaos by an information-theoretic measure of the sensitive dependence on the initial conditions

Christian Schittenkopf, G. Deco, C. Schittenkopf, 1997 .

Stochastic resonance in the mutual information between input and output spike trains of noisy central neurons

Bernd Schürmann, G. Deco, B. Schürmann, 1998 .

Investigating the underlying Markovian dynamics of ECG rhythms by information flow

G. Deco, B. Schürmann, R. Silipo, 2001 .

Blind signal separation revisited

G. Deco, D. Obradovic, 1997, Proceedings of the 36th IEEE Conference on Decision and Control.

Dynamic modeling of chaotic time series by neural networks

Gustavo Deco, Bernd Schürmann, Bernd Schürmann, 1997, Annual Conference Computational Learning Theory.

UNSUPERVISED LEARNING FOR BOLTZMANN MACHINES

Lucas C. Parra, Gustavo Deco, L. Parra, 1995 .

Information dynamics and neural techniques for data analysis

Gustavo Deco, G. Deco, 1998 .

A Nonlinear Markovian Characterization of Time Series Using Neural Networks

Gustavo Deco, Christian Schittenkopf, G. Deco, 1997, Foundations of Computer Science: Potential - Theory - Cognition.

DETERMINING THE INFORMATION FLOW OF DYNAMICAL SYSTEMS FROM CONTINUOUS PROBABILITY DISTRIBUTIONS

G. Deco, B. Schürmann, C. Schittenkopf, 1997 .

Statistical Physics Theory of Supervised Learning and Generalization

Gustavo Deco, Dragan Obradovic, G. Deco, 1996 .

A Neurodynamical Model of Visual Attention: Feedback Enhancement of Spatial Resolution in a Hierarchical System

Gustavo Deco, Josef Zihl, G. Deco, 2001, Journal of Computational Neuroscience.

Information Maximization and Independent Component Analysis: Is There a Difference?

D. Obradovic, G. Deco, G. Deco, 1998, Neural Computation.

Blind source separation: are information maximization and redundancy minimization different?

Dragan Obradovic, G. Deco, Gustavo Deco, 1997, Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop.

Unsupervised learning for blind source separation: an information-theoretic approach

Gustavo Deco, Dragan Obradovic, G. Deco, 1997, 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing.

An information theory based learning paradigm for linear feature extraction

Gustavo Deco, Dragan Obradovic, G. Deco, 1996, Neurocomputing.

Statistical Independence and Novelty Detection with Information Preserving Nonlinear Maps

Lucas C. Parra, Gustavo Deco, Stefan Miesbach, 1996, Neural Computation.

Spatiotemporal Coding in the Cortex: Information Flow-Based Learning in Spiking Neural Networks

Gustavo Deco, Bernd Schürmann, G. Deco, 1999, Neural Computation.

The coding of information by spiking neurons: an analytical study.

G Deco, B Schürmann, G. Deco, 1998, Network.

Dynamical Analysis of Time Series by Statistical Tests

Bernd Schürmann, Christian Schittenkopf, G. Deco, 1997 .

Training data selection by detecting predictability in non-stationary time series by a surrogate-cumulant based approach

B. Schurmann, G. Deco, G. Deco, 1996, Proceedings of International Workshop on Neural Networks for Identification, Control, Robotics and Signal/Image Processing.

Nonparametric Data Selection for Improvement of Parametric Neural Learning: A Cumulant-Surrogate Method

Gustavo Deco, Bernd Schürmann, G. Deco, 1996, ICANN.

Nonlinear Feature Extraction: Deterministic Neural Networks

Gustavo Deco, Dragan Obradovic, G. Deco, 1996 .

Rest EEG Hidden Dynamics as a Discriminant for Brain Tumour Classification

Gustavo Deco, Rosaria Silipo, Helmut Bartsch, 2000, Artificial Neural Networks in Biomedicine.

Dynamics extraction in multivariate biomedical time series

Gustavo Deco, Rosaria Silipo, Helmut Bartsch, 1998, Biological Cybernetics.

Unsupervised Mutual Information Criterion for Elimination of Overtraining in Supervised Multilayer Networks

Gustavo Deco, William Finnoff, Hans-Georg Zimmermann, 1995, Neural Computation.

Biased Competition Mechanisms for Visual Attention in a Multimodular Neurodynamical System

Gustavo Deco, G. Deco, 2001, Emergent Neural Computational Architectures Based on Neuroscience.

Supervised Learning and Statistical Estimation

Gustavo Deco, Dragan Obradovic, G. Deco, 1996 .

Unsupervised Learning for Boltzmann Machines 1 Unsupervised Learning for Boltzmann Machines

L. Parra, G. Deco, 2022 .

Finit Automata-Models for the Investigation of Dynamical Systems

Gustavo Deco, Wilfried Brauer, Christian Schittenkopf, 1997, Inf. Process. Lett..

G. Deco, N. York, M. Kamber, 2002, IEEE Transactions on Neural Networks.

Neural learning of chaotic dynamics

Gustavo Deco, Bernd Schürmann, G. Deco, 1995, Neural Processing Letters.

Linear Feature Extraction: Infomax Principle

Gustavo Deco, Dragan Obradovic, G. Deco, 1996 .

Non-parametric Data Selection for Neural Learning in Non-stationary Time Series

Gustavo Deco, Bernd Schürmann, Ralph Neuneier, 1997, Neural Networks.

Two Strategies to Avoid Overfitting in Feedforward Networks

Gustavo Deco, Wilfried Brauer, Christian Schittenkopf, 1997, Neural Networks.

Information Transmission and Temporal Code in Central Spiking Neurons

Bernd Schürmann, G. Deco, B. Schürmann, 1997 .

Neurodynamical mechanism of binding and selective attention for visual search

G. Deco, J. Zihl, 2000, Neurocomputing.

Predictive Coding in the Visual Cortex by a Recurrent Network with Gabor Receptive Fields

Gustavo Deco, Bernd Schürmann, G. Deco, 2001, Neural Processing Letters.

Nonlinear Feature Extraction: Boolean Stochastic Networks

Gustavo Deco, Dragan Obradovic, G. Deco, 1996 .

A characterization of HRV's nonlinear hidden dynamics by means of Markov models

G. Deco, R. Silipo, R. Vergassola, 1999, IEEE Transactions on Biomedical Engineering.

Nonlinear Modelling of the Daily Heart Rhythm

Gustavo Deco, Christian Schittenkopf, Rosaria Silipo, 1997, ICANN.

Testing nonlinear Markovian hypotheses in dynamical systems

Christian Schittenkopf, G. Deco, C. Schittenkopf, 1997 .

Detecting non-linear dynamics in financial time series

Gustavo Deco, Christian Schittenkopf, G. Deco, 1997, Proceedings of the IEEE/IAFE 1997 Computational Intelligence for Financial Engineering (CIFEr).

Feature-based Attention in Human Visual Cortex: Simulation of Fmri Data

Gustavo Deco, Silvia Corchs, G. Deco, 2003 .

Learning Exact Patterns of Quasi-synchronization among Spiking Neurons from Data on Multi-unit Recordings

Kathryn B. Laskey, Gustavo Deco, Laura Martignon, 1996, NIPS.

A Neurodynamical Approach to Visual Attention

Gustavo Deco, Josef Zihl, G. Deco, 1999, NIPS.

Neural Coding: Higher-Order Temporal Patterns in the Neurostatistics of Cell Assemblies

Kathryn B. Laskey, G. Deco, W. Freiwald, 2000, Neural Computation.