Bernhard Nessler

发表

GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium

Sepp Hochreiter, Martin Heusel, Bernhard Nessler, 2017, NIPS.

STDP enables spiking neurons to detect hidden causes of their inputs

Wolfgang Maass, Bernhard Nessler, Michael Pfeiffer, 2009, NIPS.

STDP Installs in Winner-Take-All Circuits an Online Approximation to Hidden Markov Model Learning

David Kappel, Wolfgang Maass, Bernhard Nessler, 2014, PLoS Comput. Biol..

GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium pdf

Sepp Hochreiter, Martin Heusel, Günter Klambauer, 2017, ArXiv.

Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications pdf

Sepp Hochreiter, Bernhard Nessler, Johannes Weissenbock, 2021, ArXiv.

Admission Certification for Digital Pilots in Public Traffic

Bernhard Nessler, H. Watzinger, J. Martinez-Gil, 2022 .

STDP performs stochastic EM to reveal the hidden causes of spatiotemporal spiking patterns

Wolfgang Maass, Michael Pfeiffer, Bernhard Nessler, 2009, NIPS 2009.

Local inhibition facilitates synaptic learning in spatially extended Bayesian spiking networks

Stefan Habenschuss, Wolfgang Maass, Lars Buesing, 2013 .

A Hebbian Learning Rule for Optimal Decision Making

Wolfgang Maass, Michael Pfeiffer, Bernhard Nessler, 2008 .

Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity

Wolfgang Maass, Lars Buesing, Bernhard Nessler, 2013, PLoS Comput. Biol..

The balancing principle for parameter choice in distance-regularized domain adaptation

Bernhard Nessler, Hamid Eghbal-zadeh, W. Zellinger, 2021, NeurIPS.

Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons

Wolfgang Maass, Lars Buesing, Johannes Bill, 2011, PLoS Comput. Biol..

Hebbian Learning of Bayes Optimal Decisions

Wolfgang Maass, Bernhard Nessler, Michael Pfeiffer, 2008, NIPS.

Patch Refinement - Localized 3D Object Detection pdf

Sepp Hochreiter, Thomas Adler, Andreas Mitterecker, 2019, ArXiv.

Speeding up Semantic Segmentation for Autonomous Driving

Sepp Hochreiter, Martin Heusel, Felix Friedmann, 2016 .

Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation

Sepp Hochreiter, Günter Klambauer, Markus Hofmarcher, 2019, Explainable AI.

Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields pdf

Sepp Hochreiter, Martin Heusel, Gunter Klambauer, 2017, ICLR.

Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition

Stefan Habenschuss, Wolfgang Maass, Lars Buesing, 2015, PloS one.

Reward-Modulated Hebbian Learning of Decision Making

Wolfgang Maass, Rodney J. Douglas, Bernhard Nessler, 2010, Neural Computation.

Where’s the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network

Jochen Triesch, Bernhard Nessler, Christoph Hartmann, 2015, PLoS Comput. Biol..

Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields

S. Hochreiter, Thomas Unterthiner, Hubert Ramsauer, 2017, ICLR.

GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium

S. Hochreiter, Thomas Unterthiner, Hubert Ramsauer, 2017, ArXiv.

Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints

Stefan Habenschuss, Johannes Bill, Bernhard Nessler, 2012, NIPS.