ML Anthology

Maass, Wolfgang

62 publications

NeurIPSW 2024 Incorporating Metabolic Information into LLMs for Anomaly Detection in Clinical Time-Series Maxx Richard Rahman, Ruoxuan Liu, Wolfgang Maass
IJCAI 2024 REAVER: Real-Time Earthquake Prediction with Attention-Based Sliding-Window Spectrograms Lotfy H. Abdel Khaliq, Sabine Janzen, Wolfgang Maass
IJCAI 2024 SACNN: Self Attention-Based Convolutional Neural Network for Fraudulent Behaviour Detection in Sports Maxx Richard Rahman, Lotfy H. Abdel Khaliq, Thomas Piper, Hans Geyer, Tristan Equey, Norbert Baume, Reid Aikin, Wolfgang Maass
NeurIPSW 2019 Eligibility Traces Provide a Data-Inspired Alternative to Backpropagation Through Time Guillaume Bellec, Franz Scherr, Elias Hajek, Darjan Salaj, Anand Subramoney, Robert Legenstein, Wolfgang Maass
ICLR 2018 Deep Rewiring: Training Very Sparse Deep Networks Guillaume Bellec, David Kappel, Wolfgang Maass, Robert Legenstein
NeurIPS 2018 Long Short-Term Memory and Learning-to-Learn in Networks of Spiking Neurons Guillaume Bellec, Darjan Salaj, Anand Subramoney, Robert Legenstein, Wolfgang Maass
NeurIPS 2018 Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons Nima Anari, Constantinos Daskalakis, Wolfgang Maass, Christos Papadimitriou, Amin Saberi, Santosh Vempala
NeurIPS 2015 Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring David Kappel, Stefan Habenschuss, Robert Legenstein, Wolfgang Maass
NeurIPS 2009 Functional Network Reorganization in Motor Cortex Can Be Explained by Reward-Modulated Hebbian Learning Steven Chase, Andrew Schwartz, Wolfgang Maass, Robert A. Legenstein
ICML 2009 Learning Complex Motions by Sequencing Simpler Motion Templates Gerhard Neumann, Wolfgang Maass, Jan Peters
NeurIPS 2009 Replacing Supervised Classification Learning by Slow Feature Analysis in Spiking Neural Networks Stefan Klampfl, Wolfgang Maass
NeurIPS 2009 STDP Enables Spiking Neurons to Detect Hidden Causes of Their Inputs Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
NeurIPS 2008 Hebbian Learning of Bayes Optimal Decisions Bernhard Nessler, Michael Pfeiffer, Wolfgang Maass
NeurIPS 2007 Simplified Rules and Theoretical Analysis for Information Bottleneck Optimization and PCA with Spiking Neurons Lars Buesing, Wolfgang Maass
NeurIPS 2007 Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity Dejan Pecevski, Wolfgang Maass, Robert A. Legenstein
NeurIPS 2006 Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons Stefan Klampfl, Wolfgang Maass, Robert A. Legenstein
NeurIPS 2006 Temporal Dynamics of Information Content Carried by Neurons in the Primary Visual Cortex Danko Nikolić, Stefan Haeusler, Wolf Singer, Wolfgang Maass
NeurIPS 2005 A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity Robert A. Legenstein, Wolfgang Maass
NeurIPS 2005 Principles of Real-Time Computing with Feedback Applied to Cortical Microcircuit Models Wolfgang Maass, Prashant Joshi, Eduardo D. Sontag
NeurIPS 2004 Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits Wolfgang Maass, Robert A. Legenstein, Nils Bertschinger
NeurIPS 2003 Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons Thomas Natschläger, Wolfgang Maass
NeurIPS 2002 A Model for Real-Time Computation in Generic Neural Microcircuits Wolfgang Maass, Thomas Natschläger, Henry Markram
NeCo 2002 Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations Wolfgang Maass, Thomas Natschläger, Henry Markram
NeCo 2001 Computing the Optimally Fitted Spike Train for a Synapse Thomas Natschläger, Wolfgang Maass
NeCo 2000 A Model for Fast Analog Computation Based on Unreliable Synapses Wolfgang Maass, Thomas Natschläger
NeurIPS 2000 Finding the Key to a Synapse Thomas Natschläger, Wolfgang Maass
NeurIPS 2000 Foundations for a Circuit Complexity Theory of Sensory Processing Robert A. Legenstein, Wolfgang Maass
NeCo 2000 Neural Systems as Nonlinear Filters Wolfgang Maass, Eduardo D. Sontag
NeCo 2000 On the Computational Power of Winner-Take-All Wolfgang Maass
NeurIPS 2000 Processing of Time Series by Neural Circuits with Biologically Realistic Synaptic Dynamics Thomas Natschläger, Wolfgang Maass, Eduardo D. Sontag, Anthony M. Zador
NeCo 1999 Analog Neural Nets with Gaussian or Other Common Noise Distribution Cannot Recognize Arbitrary Regular Languages Wolfgang Maass, Eduardo D. Sontag
NeCo 1999 Dynamic Stochastic Synapses as Computational Units Wolfgang Maass, Anthony M. Zador
NeurIPS 1999 Neural Computation with Winner-Take-All as the Only Nonlinear Operation Wolfgang Maass
NeurIPS 1998 A Precise Characterization of the Class of Languages Recognized by Neural Nets Under Gaussian and Other Common Noise Distributions Wolfgang Maass, Eduardo D. Sontag
NeCo 1998 On the Effect of Analog Noise in Discrete-Time Analog Computations Wolfgang Maass, Pekka Orponen
NeurIPS 1997 Dynamic Stochastic Synapses as Computational Units Wolfgang Maass, Anthony M. Zador
NeCo 1997 Fast Sigmoidal Networks via Spiking Neurons Wolfgang Maass
COLT 1997 On the Complexity of Learning for a Spiking Neuron (Extended Abstract) Wolfgang Maass, Michael Schmitt
ALT 1997 On the Relevance of Time in Neural Computation and Learning Wolfgang Maass
COLT 1996 Learning of Depth Two Neural Networks with Constant Fan-in at the Hidden Nodes (Extended Abstract) Peter Auer, Stephen Kwek, Wolfgang Maass, Manfred K. Warmuth
NeCo 1996 Lower Bounds for the Computational Power of Networks of Spiking Neurons Wolfgang Maass
NeurIPS 1996 Noisy Spiking Neurons with Temporal Coding Have More Computational Power than Sigmoidal Neurons Wolfgang Maass
NeurIPS 1996 On the Effect of Analog Noise in Discrete-Time Analog Computations Wolfgang Maass, Pekka Orponen
NeCo 1995 Agnostic PAC Learning of Functions on Analog Neural Nets Wolfgang Maass
ICML 1995 Efficient Learning with Virtual Threshold Gates Wolfgang Maass, Manfred K. Warmuth
MLJ 1995 On the Complexity of Function Learning Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger
NeurIPS 1995 On the Computational Power of Noisy Spiking Neurons Wolfgang Maass
COLT 1995 Proceedings of the Eigth Annual Conference on Computational Learning Theory, COLT 1995, Santa Cruz, California, USA, July 5-8, 1995 Wolfgang Maass
ICML 1995 Theory and Applications of Agnostic PAC-Learning with Small Decision Trees Peter Auer, Robert C. Holte, Wolfgang Maass
MLJ 1994 Algorithms and Lower Bounds for On-Line Learning of Geometrical Concepts Wolfgang Maass, György Turán
COLT 1994 Efficient Agnostic PAC-Learning with Simple Hypothesis Wolfgang Maass
NeCo 1994 Neural Nets with Superlinear VC-Dimension Wolfgang Maass
NeurIPS 1994 On the Computational Complexity of Networks of Spiking Neurons Wolfgang Maass
MLJ 1994 On-Line Learning of Rectangles and Unions of Rectangles Zhixiang Chen, Wolfgang Maass
NeurIPS 1993 Agnostic PAC-Learning of Functions on Analog Neural Nets Wolfgang Maass
COLT 1993 On the Complexity of Function Learning Peter Auer, Philip M. Long, Wolfgang Maass, Gerhard J. Woeginger
MLJ 1992 Lower Bound Methods and Separation Results for On-Line Learning Models Wolfgang Maass, György Turán
COLT 1992 On-Line Learning of Rectangles Zhixiang Chen, Wolfgang Maass
COLT 1991 Fast Identification of Geometric Objects with Membership Queries William J. Bultman, Wolfgang Maass
COLT 1991 On-Line Learning with an Oblivious Environment and the Power of Randomization Wolfgang Maass
NeurIPS 1990 A Method for the Efficient Design of Boltzmann Machines for Classiffication Problems Ajay Gupta, Wolfgang Maass
COLT 1990 On the Complexity of Learning from Counterexamples and Membership Queries (abstract) Wolfgang Maass, György Turán