| 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 | 2395 | 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 | 2395 | 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 | 364 | 2011 |
| 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 | 234 | 2013 |
| Speeding up Semantic Segmentation for Autonomous Driving M Treml, J Arjona-Medina, T Unterthiner, R Durgesh, F Friedmann, ... | 140 | 2016 |
| 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 | 110 | 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 | 91 | 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 | 48 | 2017 |
| 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 | 36 | 2015 |
| 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 | 30 | 2012 |
| Reward-modulated hebbian learning of decision making M Pfeiffer, B Nessler, RJ Douglas, W Maass Neural Computation 22 (6), 1399-1444, 2010 | 30 | 2010 |
| Patch Refinement--Localized 3D Object Detection J Lehner, A Mitterecker, T Adler, M Hofmarcher, B Nessler, S Hochreiter arXiv preprint arXiv:1910.04093, 2019 | 15 | 2019 |
| 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 | 15 | 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 | 15 | 2015 |
| Hebbian learning of Bayes optimal decisions B Nessler, M Pfeiffer, W Maass Advances in neural information processing systems, 1169-1176, 2009 | 13 | 2009 |
| 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 | 9 | 2019 |
| Visual Scene Understanding for Autonomous Driving Using Semantic Segmentation G Klambauer, S Hochreiter, B Nessler Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 285, 0 | 9* | |
| MEDICAL STRIP ELECTRODE J Fortin, W Nessler, B Nessler, F Skrabal EP Patent 1,377,212, 2005 | 1 | 2005 |
| Medical strip electrode J Fortin, W Nessler, B Nessler, F Skrabal US Patent App. 10/660,002, 2003 | 1 | 2003 |
| MEDICAL STRIP ELECTRODE J FORTIN, W NESSLER, B NESSLER, F SKRABAL WO Patent WO/2002/071,940, 2002 | 1 | 2002 |
Wolfgang MaassProfessor of Computer Science, Graz University of TechnologyVerified email at igi.tugraz.at
