no code implementations • 4 Oct 2023 • Bernhard Nessler, Thomas Doms, Sepp Hochreiter
The authors are concerned about the safety, health, and rights of the European citizens due to inadequate measures and procedures required by the current draft of the EU Artificial Intelligence (AI) Act for the conformity assessment of AI systems.
1 code implementation • NeurIPS 2021 • Werner Zellinger, Natalia Shepeleva, Marius-Constantin Dinu, Hamid Eghbal-zadeh, Hoan Nguyen, Bernhard Nessler, Sergei Pereverzyev, Bernhard A. Moser
Our approach starts with the observation that the widely-used method of minimizing the source error, penalized by a distance measure between source and target feature representations, shares characteristics with regularized ill-posed inverse problems.
no code implementations • 31 Mar 2021 • Philip Matthias Winter, Sebastian Eder, Johannes Weissenböck, Christoph Schwald, Thomas Doms, Tom Vogt, Sepp Hochreiter, Bernhard Nessler
Artificial Intelligence is one of the fastest growing technologies of the 21st century and accompanies us in our daily lives when interacting with technical applications.
no code implementations • 9 Oct 2019 • Johannes Lehner, Andreas Mitterecker, Thomas Adler, Markus Hofmarcher, Bernhard Nessler, Sepp Hochreiter
We introduce Patch Refinement a two-stage model for accurate 3D object detection and localization from point cloud data.
Ranked #1 on Object Detection on KITTI Cars Moderate
1 code implementation • ICLR 2018 • Thomas Unterthiner, Bernhard Nessler, Calvin Seward, Günter Klambauer, Martin Heusel, Hubert Ramsauer, Sepp Hochreiter
We prove that Coulomb GANs possess only one Nash equilibrium which is optimal in the sense that the model distribution equals the target distribution.
67 code implementations • NeurIPS 2017 • Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, Sepp Hochreiter
Generative Adversarial Networks (GANs) excel at creating realistic images with complex models for which maximum likelihood is infeasible.
Ranked #1 on Image Generation on LSUN Bedroom 64 x 64
2 code implementations • 1 Jun 2016 • Michael Treml, Jose A. Arjona-Medina, Thomas Unterthiner, Rupesh Durgesh, Felix Friedmann, Peter Schuberth, Andreas Mayr, Martin Heusel, Markus Hofmarcher, Michael Widrich, Bernhard Nessler, Sepp Hochreiter
We propose a novel deep network architecture for image segmentation that keeps the high accuracy while being efficient enough for embedded devices.
no code implementations • NeurIPS 2012 • Stefan Habenschuss, Johannes Bill, Bernhard Nessler
Recent spiking network models of Bayesian inference and unsupervised learning frequently assume either inputs to arrive in a special format or employ complex computations in neuronal activation functions and synaptic plasticity rules.
no code implementations • NeurIPS 2009 • Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
We show here that STDP, in conjunction with a stochastic soft winner-take-all (WTA) circuit, induces spiking neurons to generate through their synaptic weights implicit internal models for subclasses (or causes") of the high-dimensional spike patterns of hundreds of pre-synaptic neurons.
no code implementations • NeurIPS 2008 • Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
Uncertainty is omnipresent when we perceive or interact with our environment, and the Bayesian framework provides computational methods for dealing with it.