Bernhard Nessler

19 papers A* 1Journal 12Unranked 5

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Proceedings of 1st Workshop on Advancing Artificial Intelligence through Theory of Mind. CoRR Mouad Abrini, Omri Abend, Dina M. Acklin, Henny Admoni, Gregor Aichinger, Nitay Alon, Zahra Ashktorab, Ashish Atreja, Moises Auron, Alexander Aufreiter, Raghav Awasthi, Soumya Banerjee, Joseph M. Barnby, Rhea Basappa, Severin Bergsmann, Djallel Bouneffouf, Patrick Callaghan, Marc Cavazza, Thierry Chaminade, Sonia Chernova, Mohamed Chetouani, Moumita Choudhury, Axel Cleeremans, Jacek B. Cywinski, Fabio Cuzzolin, Hokin Deng, N'yoma Diamond, Camilla Di Pasquasio, Guillaume Dumas, Max J. van Duijn, Mahapatra Dwarikanath, Qingying Gao, Ashok K. Goel, Rebecca Goldstein, Matthew C. Gombolay, Gabriel Enrique Gonzalez, Amar Halilovic, Tobias Halmdienst, Mahimul Islam, Julian Jara-Ettinger, Natalie Kastel, Renana Keydar, Ashish K. Khanna, Mahdi Khoramshahi, Jihyun Kim, MiHyeon Kim, YoungBin Kim, Senka Krivic, Nikita Krasnytskyi, Arun Kumar, JuneHyoung Kwon, Eunju Lee, Shane Lee, Peter R. Lewis, Xue Li, Yijiang Li, Michal Lewandowski, Nathan Lloyd, Matthew B. Luebbers, Dezhi Luo, Haiyun Lyu, Dwarikanath Mahapatra, Kamal Maheshwari, Mallika Mainali, Piyush Mathur, Patrick Mederitsch, Shuwa Miura, Manuel Preston de Miranda, Reuth Mirsky, Shreya Mishra, Nina Moorman, Katelyn Morrison, John Muchovej, Bernhard Nessler, Felix Nessler, Hieu Minh Jord Nguyen, Abby Ortego, Francis A. Papay, Antoine Pasquali, Hamed Rahimi, Charumathi Raghu, Amanda L. Royka, Stefan Sarkadi, Jaelle Scheuerman, Simon Schmid, Paul Schrater, Anik Sen, Zahra Sheikhbahaee, Ke Shi, Reid G. Simmons, Nishant Singh, Mason O. Smith, Ramira van der Meulen, Anthia Solaki, Haoran Sun, Viktor Szolga, Matthew E. Taylor, Travis Taylor, Sanne van Waveren, Juan David Vargas
2025	J	`jnl`	Safe and Certifiable AI Systems: Concepts, Challenges, and Lessons Learned. CoRR Kajetan Schweighofer, Barbara Brune, Lukas Gruber, Simon Schmid, Alexander Aufreiter, Andreas Gruber, Thomas Doms, Sebastian Eder, Florian Mayer, Xaver-Paul Stadlbauer, Christoph Schwald, Werner Zellinger, Bernhard Nessler, Sepp Hochreiter
2023	J	`jnl`	Functional trustworthiness of AI systems by statistically valid testing. CoRR Bernhard Nessler, Thomas Doms, Sepp Hochreiter
2021	A*	`conf`	The balancing principle for parameter choice in distance-regularized domain adaptation. NeurIPS Werner Zellinger, Natalia Shepeleva, Marius-Constantin Dinu, Hamid Eghbal-zadeh, Hoan Duc Nguyen, Bernhard Nessler, Sergei V. Pereverzyev, Bernhard Alois Moser
2021	J	`jnl`	Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications. CoRR Philip Matthias Winter, Sebastian Eder, Johannes Weissenböck, Christoph Schwald, Thomas Doms, Tom Vogt, Sepp Hochreiter, Bernhard Nessler
2019	J	`jnl`	Patch Refinement - Localized 3D Object Detection. CoRR Johannes Lehner, Andreas Mitterecker, Thomas Adler, Markus Hofmarcher, Bernhard Nessler, Sepp Hochreiter
2019	—	`ch.`	Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation. Explainable AI Markus Hofmarcher, Thomas Unterthiner, Jose A. Arjona-Medina, Günter Klambauer, Sepp Hochreiter, Bernhard Nessler
2018	—	`conf`	Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields. ICLR (Poster) Thomas Unterthiner, Bernhard Nessler, Calvin Seward, Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter
2017	J	`jnl`	Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields. CoRR Thomas Unterthiner, Bernhard Nessler, Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter
2017	—	`conf`	GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium. NIPS Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Sepp Hochreiter
2017	J	`jnl`	GANs Trained by a Two Time-Scale Update Rule Converge to a Nash Equilibrium. CoRR Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Günter Klambauer, Sepp Hochreiter
2015	J	`jnl`	Where's the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network. PLoS Comput. Biol. Christoph Hartmann, Andreea Lazar, Bernhard Nessler, Jochen Triesch
2014	J	`jnl`	STDP Installs in Winner-Take-All Circuits an Online Approximation to Hidden Markov Model Learning. PLoS Comput. Biol. David Kappel, Bernhard Nessler, Wolfgang Maass
2013	J	`jnl`	Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity. PLoS Comput. Biol. Bernhard Nessler, Michael Pfeiffer, Lars Buesing, Wolfgang Maass
2012	—	`conf`	Homeostatic plasticity in Bayesian spiking networks as Expectation Maximization with posterior constraints. NIPS Stefan Habenschuss, Johannes Bill, Bernhard Nessler
2011	J	`jnl`	Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons. PLoS Comput. Biol. Lars Buesing, Johannes Bill, Bernhard Nessler, Wolfgang Maass
2010	J	`jnl`	Reward-Modulated Hebbian Learning of Decision Making. Neural Comput. Michael Pfeiffer, Bernhard Nessler, Rodney J. Douglas, Wolfgang Maass
2009	—	`conf`	STDP enables spiking neurons to detect hidden causes of their inputs. NIPS Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
2008	—	`conf`	Hebbian Learning of Bayes Optimal Decisions. NIPS Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass