Bernhard Nessler

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Sepp HochreiterInstitute for Machine Learning, Johannes Kepler University LinzDirección de correo verificada de ml.jku.at
Thomas UnterthinerGoogle DeepMindDirección de correo verificada de pm.me
Martin HeuselZalando ResearchDirección de correo verificada de zalando.de
Hubert RamsauerResearch Assistant at Institute for Machine Learning, Johannes Kepler University LinzDirección de correo verificada de ml.jku.at
Wolfgang MaassProfessor of Computer Science, Graz University of TechnologyDirección de correo verificada de igi.tugraz.at
Michael PfeifferBosch Center for Artificial IntelligenceDirección de correo verificada de de.bosch.com
Lars BuesingGoogle DeepMindDirección de correo verificada de google.com
Johannes BillHarvard Medical SchoolDirección de correo verificada de hms.harvard.edu
Markus HofmarcherInstitute for Machine Learning, Johannes Kepler University LinzDirección de correo verificada de ml.jku.at
Jose A. Arjona-MedinaJanssenDirección de correo verificada de its.jnj.com
Michael WidrichMachine Learning Scientist @ FreenomeDirección de correo verificada de freenome.com
Andreas MayrInstitute for Machine Learning, Johannes Kepler University LinzDirección de correo verificada de ml.jku.at
Günter KlambauerProf., LIT AI Lab & Institute for Machine Learning, Johannes Kepler UniversityDirección de correo verificada de ml.jku.at
David KappelBielefeld UniversityDirección de correo verificada de uni-bielefeld.de
Rodney DouglasProfessor of Computational NeuroscienceDirección de correo verificada de ini.phys.ethz.ch
Calvin SewardZalando ResearchDirección de correo verificada de zalando.de
Andreas MittereckerDirección de correo verificada de ml.jku.at
Thomas AdlerJohannes Kepler University, LinzDirección de correo verificada de ml.jku.at
Johannes LehnerJohannes Kepler Universität LinzDirección de correo verificada de ml.jku.at
Andreea LazarErnst Strüngmann Institute for NeuroscienceDirección de correo verificada de brain.mpg.de

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Bernhard Nessler

SCCH GmbH & Johannes Kepler University Linz, Austria

Dirección de correo verificada de scch.at

Computational Neuroscience Machine Learning Deep Learning Autonomous Driving


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Gans trained by a two time-scale update rule converge to a local nash equilibrium M Heusel, H Ramsauer, T Unterthiner, B Nessler, S Hochreiter Advances in Neural Information Processing Systems, 6626-6637, 2017	14398	2017
GANs trained by a two time-scale update rule converge to a local nash equilibrium M Heusel, H Ramsauer, T Unterthiner, B Nessler, S Hochreiter Advances in Neural Information Processing Systems, 6629-6640, 2017	14398	2017
Neural dynamics as sampling: A model for stochastic computation in recurrent networks of spiking neurons L Buesing, J Bill, B Nessler, W Maass PLoS Computational Biology 7 (11), e1002211, 2011	509	2011
Speeding up Semantic Segmentation for Autonomous Driving M Treml, J Arjona-Medina, T Unterthiner, R Durgesh, F Friedmann, ...	352	2016
Bayesian computation emerges in generic cortical microcircuits through spike-timing-dependent plasticity B Nessler, M Pfeiffer, L Buesing, W Maass PLoS computational biology 9 (4), e1003037, 2013	336	2013
STDP enables spiking neurons to detect hidden causes of their inputs B Nessler, M Pfeiffer, W Maass Advances in Neural Information Processing Systems 22, 1357-1365, 2009	151	2009
STDP installs in winner-take-all circuits an online approximation to hidden markov model learning D Kappel, B Nessler, W Maass PLoS computational biology 10 (3), e1003511, 2014	132	2014
Coulomb GANs: Provably optimal nash equilibria via potential fields T Unterthiner, B Nessler, C Seward, G Klambauer, M Heusel, ... arXiv preprint arXiv:1708.08819, 2017	84	2017
Gans trained by a two time-scale update rule converge to a local nash equilibrium. arXiv 2017 M Heusel, H Ramsauer, T Unterthiner, B Nessler, S Hochreiter arXiv preprint arXiv:1706.08500, 0	71
Patch Refinement--Localized 3D Object Detection J Lehner, A Mitterecker, T Adler, M Hofmarcher, B Nessler, S Hochreiter arXiv preprint arXiv:1910.04093, 2019	69	2019
Where’s the noise? key features of spontaneous activity and neural variability arise through learning in a deterministic network C Hartmann, A Lazar, B Nessler, J Triesch PLoS computational biology 11 (12), e1004640, 2015	67	2015
Visual scene understanding for autonomous driving using semantic segmentation M Hofmarcher, T Unterthiner, J Arjona-Medina, G Klambauer, ... Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 285-296, 2019	61	2019
Visual scene understanding for autonomous driving using semantic segmentation M Hofmarcher, T Unterthiner, J Arjona-Medina, G Klambauer, ... Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 285-296, 2019	61	2019
Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints S Habenschuss, J Bill, B Nessler Advances in Neural Information Processing Systems, 773-781, 2012	40	2012
Reward-modulated hebbian learning of decision making M Pfeiffer, B Nessler, RJ Douglas, W Maass Neural Computation 22 (6), 1399-1444, 2010	39	2010
Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications PM Winter, S Eder, J Weissenböck, C Schwald, T Doms, T Vogt, ... arXiv preprint arXiv:2103.16910, 2021	35	2021
Distributed bayesian computation and self-organized learning in sheets of spiking neurons with local lateral inhibition J Bill, L Buesing, S Habenschuss, B Nessler, W Maass, R Legenstein PloS one 10 (8), e0134356, 2015	29	2015
Distributed Bayesian computation and self-organized learning in sheets of spiking neurons with local lateral inhibition J Bill, L Buesing, S Habenschuss, B Nessler, W Maass, R Legenstein PloS one 10 (8), e0134356, 2015	29	2015
Hebbian learning of Bayes optimal decisions B Nessler, M Pfeiffer, W Maass Advances in neural information processing systems, 1169-1176, 2009	19	2009
The balancing principle for parameter choice in distance-regularized domain adaptation W Zellinger, N Shepeleva, MC Dinu, H Eghbal-zadeh, HD Nguyen, ... Advances in Neural Information Processing Systems 34, 20798-20811, 2021	14	2021

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