Laurenz Wiskott

ORCID

Publication Activity (10 Years)

Years Active: 1990-2024
Publications (10 Years): 53

Top Venues

Ruhr University Bochum, Germany (PHD)

Education History

Ruhr University Bochum, Germany

PHD

Publications

Robin Schiewer, Anand Subramoney, Laurenz Wiskott
Exploring the limits of Hierarchical World Models in Reinforcement Learning. CoRR (2024)
Malte Schilling, Barbara Hammer, Frank W. Ohl, Helge J. Ritter, Laurenz Wiskott
Modularity in Nervous Systems - a Key to Efficient Adaptivity for Deep Reinforcement Learning. Cogn. Comput. 16 (5) (2024)
Jan Rathjens, Laurenz Wiskott
Classification and Reconstruction Processes in Deep Predictive Coding Networks: Antagonists or Allies? CoRR (2024)
Frederik Baucks, Robin Schmucker, Laurenz Wiskott
Gaining Insights into Course Difficulty Variations Using Item Response Theory. LAK (2024)
Max Bauroth, Pavlos Rath-Manakidis, Valentin Langholf, Laurenz Wiskott, Tobias Glasmachers
tachAId - An interactive tool supporting the design of human-centered AI solutions. Frontiers Artif. Intell. 7 (2024)
Pavlos Rath-Manakidis, Frederik Strothmann, Tobias Glasmachers, Laurenz Wiskott
ProtoP-OD: Explainable Object Detection with Prototypical Parts. CoRR (2024)
Frederik Baucks, Robin Schmucker, Conrad Borchers, Zachary A. Pardos, Laurenz Wiskott
Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning. L@S (2024)
Moritz Lange, Raphael C. Engelhardt, Wolfgang Konen, Laurenz Wiskott
Interpretable Brain-Inspired Representations Improve RL Performance on Visual Navigation Tasks. CoRR (2024)
Frederik Baucks, Robin Schmucker, Conrad Borchers, Zachary A. Pardos, Laurenz Wiskott
Gaining Insights into Group-Level Course Difficulty via Differential Course Functioning. CoRR (2024)
Moritz Lange, Noah Krystiniak, Raphael C. Engelhardt, Wolfgang Konen, Laurenz Wiskott
Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-visual Environments: A Comparison. LOD (2) (2023)
Eddie Seabrook, Laurenz Wiskott
A Tutorial on the Spectral Theory of Markov Chains. Neural Comput. 35 (11) (2023)
Moritz Lange, Noah Krystiniak, Raphael C. Engelhardt, Wolfgang Konen, Laurenz Wiskott
Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-Visual Environments: A Comparison. CoRR (2023)
Frederik Baucks, Jonas Leschke, Christian Metzger, Laurenz Wiskott
Ein Dashboard für die Studienberatung: Technische Infrastruktur und Studienverlaufsplanung im Projekt KI: edu.nrw. DELFI Workshops (2023)
Raphael C. Engelhardt, Ralitsa Raycheva, Moritz Lange, Laurenz Wiskott, Wolfgang Konen
Ökolopoly: Case Study on Large Action Spaces in Reinforcement Learning. LOD (2) (2023)
Frederik Baucks, Laurenz Wiskott
Mitigating Biases using an Additive Grade Point Model: Towards Trustworthy Curriculum Analytics Measures. DELFI (2023)
Raphael C. Engelhardt, Marc Oedingen, Moritz Lange, Laurenz Wiskott, Wolfgang Konen
Iterative Oblique Decision Trees Deliver Explainable RL Models. Algorithms 16 (6) (2023)
Pavlos Rath-Manakidis, Hlynur Davíð Hlynsson, Laurenz Wiskott
Reduction of Variance-related Error through Ensembling: Deep Double Descent and Out-of-Distribution Generalization. ICPRAM (2022)
Raphael C. Engelhardt, Moritz Lange, Laurenz Wiskott, Wolfgang Konen
Sample-Based Rule Extraction for Explainable Reinforcement Learning. LOD (1) (2022)
Eddie Seabrook, Laurenz Wiskott
A Tutorial on the Spectral Theory of Markov Chains. CoRR (2022)
Frederik Baucks, Laurenz Wiskott
Simulating Policy Changes in Prerequisite-Free Curricula: A Supervised Data-Driven Approach. EDM (2022)
Hlynur Davíð Hlynsson, Merlin Schüler, Robin Schiewer, Tobias Glasmachers, Laurenz Wiskott
Latent Representation Prediction Networks. Int. J. Pattern Recognit. Artif. Intell. 36 (1) (2022)
Zahra Fayyaz, Aya Altamimi, Carina Zoellner, Nicole Klein, Oliver T. Wolf, Sen Cheng, Laurenz Wiskott
A Model of Semantic Completion in Generative Episodic Memory. Neural Comput. 34 (9) (2022)
Hlynur Davíð Hlynsson, Laurenz Wiskott
Reward prediction for representation learning and reward shaping. CoRR (2021)
Robin Schiewer, Laurenz Wiskott
Modular Networks Prevent Catastrophic Interference in Model-Based Multi-Task Reinforcement Learning. CoRR (2021)
Robin Schiewer, Laurenz Wiskott
Modular Networks Prevent Catastrophic Interference in Model-Based Multi-task Reinforcement Learning. LOD (2021)
Zahra Fayyaz, Aya Altamimi, Sen Cheng, Laurenz Wiskott
A model of semantic completion in generative episodic memory. CoRR (2021)
Max Menne, Merlin Schüler, Laurenz Wiskott
Exploring Slow Feature Analysis for Extracting Generative Latent Factors. ICPRAM (2021)
Hlynur Davíð Hlynsson, Laurenz Wiskott
Reward Prediction for Representation Learning and Reward Shaping. IJCCI (2021)
Alberto N. Escalante-B., Laurenz Wiskott
Improved graph-based SFA: information preservation complements the slowness principle. Mach. Learn. 109 (5) (2020)
Hlynur Davíð Hlynsson, Merlin Schüler, Robin Schiewer, Tobias Glasmachers, Laurenz Wiskott
Latent Representation Prediction Networks. CoRR (2020)
Stefan Richthofer, Laurenz Wiskott
Singular Sturm-Liouville Problems with Zero Potential (q=0) and Singular Slow Feature Analysis. CoRR (2020)
Jan Bollenbacher, Florian Soulier, Beate Rhein, Laurenz Wiskott
Investigating Parallelization of MAML. DS (2020)
Laurenz Wiskott, Fabian Schönfeld
Laplacian Matrix for Dimensionality Reduction and Clustering. CoRR (2019)
Laurenz Wiskott, Fabian Schönfeld
Laplacian Matrix for Dimensionality Reduction and Clustering. eBISS (2019)
Jan Melchior, Mehdi Bayati, Amir Hossein Azizi, Sen Cheng, Laurenz Wiskott
A Hippocampus Model for Online One-Shot Storage of Pattern Sequences. CoRR (2019)
Hlynur Davíð Hlynsson, Laurenz Wiskott
Learning Gradient-Based ICA by Neurally Estimating Mutual Information. KI (2019)
Hlynur Davíð Hlynsson, Laurenz Wiskott
Learning gradient-based ICA by neurally estimating mutual information. CoRR (2019)
Hlynur Davíð Hlynsson, Alberto N. Escalante-B., Laurenz Wiskott
Measuring the Data Efficiency of Deep Learning Methods. ICPRAM (2019)
Merlin Schüler, Hlynur Davíð Hlynsson, Laurenz Wiskott
Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening. ACML (2019)
Jan Melchior, Laurenz Wiskott
Hebbian-Descent. CoRR (2019)
Hlynur Davíð Hlynsson, Alberto N. Escalante-B., Laurenz Wiskott
Measuring the Data Efficiency of Deep Learning Methods. CoRR (2019)
Jan Freiwald, Mahdie Karbasi, Steffen Zeiler, Jan Melchior, Varun Raj Kompella, Laurenz Wiskott, Dorothea Kolossa
Utilizing Slow Feature Analysis for Lipreading. ITG Symposium on Speech Communication (2018)
Björn Weghenkel, Laurenz Wiskott
Slowness as a Proxy for Temporal Predictability: An Empirical Comparison. Neural Comput. 30 (5) (2018)
Stefan Richthofer, Laurenz Wiskott
Global Navigation Using Predictable and Slow Feature Analysis in Multiroom Environments, Path Planning and Other Control Tasks. CoRR (2018)
Jing Fang, Naima Rüther, Christian Bellebaum, Laurenz Wiskott, Sen Cheng
The Interaction between Semantic Representation and Episodic Memory. Neural Comput. 30 (2) (2018)
Merlin Schüler, Hlynur Davíð Hlynsson, Laurenz Wiskott
Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening. CoRR (2018)
Varun Raj Kompella, Laurenz Wiskott
Intrinsically Motivated Acquisition of Modular Slow Features for Humanoids in Continuous and Non-Stationary Environments. CoRR (2017)
Björn Weghenkel, Asja Fischer, Laurenz Wiskott
Graph-based predictable feature analysis. Mach. Learn. 106 (9-10) (2017)
Stefan Richthofer, Laurenz Wiskott
PFAx: Predictable Feature Analysis to Perform Control. CoRR (2017)
Björn Weghenkel, Asja Fischer, Laurenz Wiskott
Graph-based Predictable Feature Analysis. CoRR (2016)
Alberto N. Escalante-B., Laurenz Wiskott
Theoretical Analysis of the Optimal Free Responses of Graph-Based SFA for the Design of Training Graphs. J. Mach. Learn. Res. 17 (2016)
Alberto N. Escalante-B., Laurenz Wiskott
Improved graph-based SFA: Information preservation complements the slowness principle. CoRR (2016)
Jan Melchior, Asja Fischer, Laurenz Wiskott
How to Center Deep Boltzmann Machines. J. Mach. Learn. Res. 17 (2016)
Fabian Schönfeld, Laurenz Wiskott
Modeling place field activity with hierarchical slow feature analysis. Frontiers Comput. Neurosci. 9 (2015)
Alberto N. Escalante-B., Laurenz Wiskott
Theoretical Analysis of the Optimal Free Responses of Graph-Based SFA for the Design of Training Graphs. CoRR (2015)
Torsten Neher, Sen Cheng, Laurenz Wiskott
Memory Storage Fidelity in the Hippocampal Circuit: The Role of Subregions and Input Statistics. PLoS Comput. Biol. 11 (5) (2015)
Stefan Richthofer, Laurenz Wiskott
Predictable Feature Analysis. ICMLA (2015)
Laurenz Wiskott, Rolf P. Würtz, Günter Westphal
Elastic Bunch Graph Matching. Scholarpedia 9 (3) (2014)
Henning Sprekeler, Tiziano Zito, Laurenz Wiskott
An extension of slow feature analysis for nonlinear blind source separation. J. Mach. Learn. Res. 15 (1) (2014)
Björn Weghenkel, Laurenz Wiskott
Learning predictive partitions for continuous feature spaces. ESANN (2014)
Sven Dähne, Niko Wilbert, Laurenz Wiskott
Slow Feature Analysis on Retinal Waves Leads to V1 Complex Cells. PLoS Comput. Biol. 10 (5) (2014)
Nan Wang, Laurenz Wiskott, Dirk Jancke
Modeling correlations in spontaneous activity of visual cortex with centered Gaussian-binary deep Boltzmann machines. ICLR (Workshop Poster) (2014)
Nan Wang, Jan Melchior, Laurenz Wiskott
Gaussian-binary Restricted Boltzmann Machines on Modeling Natural Image Statistics. CoRR (2014)
Amir Hossein Azizi, Laurenz Wiskott, Sen Cheng
A computational model for preplay in the hippocampus. Frontiers Comput. Neurosci. 7 (2013)
Norbert Krüger, Peter Janssen, Sinan Kalkan, Markus Lappe, Ales Leonardis, Justus H. Piater, Antonio Jose Rodríguez-Sánchez, Laurenz Wiskott
Deep Hierarchies in the Primate Visual Cortex: What Can We Learn for Computer Vision? IEEE Trans. Pattern Anal. Mach. Intell. 35 (8) (2013)
Stefan Richthofer, Laurenz Wiskott
Predictable Feature Analysis. CoRR (2013)
Ha Quang Minh, Laurenz Wiskott
Multivariate Slow Feature Analysis and Decorrelation Filtering for Blind Source Separation. IEEE Trans. Image Process. 22 (7) (2013)
Alberto N. Escalante, Laurenz Wiskott
How to solve classification and regression problems on high-dimensional data with a supervised extension of slow feature analysis. J. Mach. Learn. Res. 14 (1) (2013)
Niko Wilbert, Tiziano Zito, Rike-Benjamin Schuppner, Zbigniew Jedrzejewski-Szmek, Laurenz Wiskott, Pietro Berkes
Building extensible frameworks for data processing: The case of MDP, Modular toolkit for Data Processing. J. Comput. Sci. 4 (5) (2013)
Fabian Schönfeld, Laurenz Wiskott
RatLab: an easy to use tool for place code simulations. Frontiers Comput. Neurosci. 7 (2013)
Jan Melchior, Asja Fischer, Nan Wang, Laurenz Wiskott
How to Center Binary Restricted Boltzmann Machines. CoRR (2013)
Nan Wang, Jan Melchior, Laurenz Wiskott
An analysis of Gaussian-binary restricted Boltzmann machines for natural images. ESANN (2012)
Alberto N. Escalante, Laurenz Wiskott
Slow Feature Analysis: Perspectives for Technical Applications of a Versatile Learning Algorithm. Künstliche Intell. 26 (4) (2012)
Alberto N. Escalante, Laurenz Wiskott
Heuristic Evaluation of Expansions for Non-linear Hierarchical Slow Feature Analysis. ICMLA (1) (2011)
Henning Sprekeler, Laurenz Wiskott
A Theory of Slow Feature Analysis for Transformation-Based Input Signals with an Application to Complex Cells. Neural Comput. 23 (2) (2011)
Mathias Franzius, Niko Wilbert, Laurenz Wiskott
Invariant Object Recognition and Pose Estimation with Slow Feature Analysis. Neural Comput. 23 (9) (2011)
Ha Quang Minh, Laurenz Wiskott
Slow feature analysis and decorrelation filtering for separating correlated sources. ICCV (2011)
Peter A. Appleby, Gerd Kempermann, Laurenz Wiskott
The Role of Additive Neurogenesis and Synaptic Plasticity in a Hippocampal Memory Model with Grid-Cell Like Input. PLoS Comput. Biol. 7 (1) (2011)
Laurenz Wiskott, Pietro Berkes, Mathias Franzius, Henning Sprekeler, Niko Wilbert
Slow feature analysis. Scholarpedia 6 (4) (2011)
Alberto N. Escalante, Laurenz Wiskott
Gender and Age Estimation from Synthetic Face Images. IPMU (2010)
Robert Legenstein, Niko Wilbert, Laurenz Wiskott
Reinforcement Learning on Slow Features of High-Dimensional Input Streams. PLoS Comput. Biol. 6 (8) (2010)
Mathias Franzius, Niko Wilbert, Laurenz Wiskott
Invariant Object Recognition with Slow Feature Analysis. ICANN (1) (2008)
Tiziano Zito, Niko Wilbert, Laurenz Wiskott, Pietro Berkes
Modular toolkit for Data Processing (MDP): a Python data processing framework. Frontiers Neuroinformatics 2 (2008)
Henning Sprekeler, Christian Michaelis, Laurenz Wiskott
Slowness: An Objective for Spike-Timing-Dependent Plasticity? PLoS Comput. Biol. 3 (6) (2007)
Tobias Blaschke, Tiziano Zito, Laurenz Wiskott
Independent Slow Feature Analysis and Nonlinear Blind Source Separation. Neural Comput. 19 (4) (2007)
Mathias Franzius, Henning Sprekeler, Laurenz Wiskott
Slowness and Sparseness Lead to Place, Head-Direction, and Spatial-View Cells. PLoS Comput. Biol. 3 (8) (2007)
Mathias Franzius, Roland Vollgraf, Laurenz Wiskott
From grids to places. J. Comput. Neurosci. 22 (3) (2007)
Tobias Blaschke, Pietro Berkes, Laurenz Wiskott
What Is the Relation Between Slow Feature Analysis and Independent Component Analysis? Neural Comput. 18 (10) (2006)
Pietro Berkes, Laurenz Wiskott
On the Analysis and Interpretation of Inhomogeneous Quadratic Forms as Receptive Fields. Neural Comput. 18 (8) (2006)
Tobias Blaschke, Laurenz Wiskott
Independent Slow Feature Analysis and Nonlinear Blind Source Separation. ICA (2004)
Tobias Blaschke, Laurenz Wiskott
Nonlinear Blind Source Separation by Integrating Independent Component Analysis and Slow Feature Analysis. NIPS (2004)
Tobias Blaschke, Laurenz Wiskott
CuBICA: independent component analysis by simultaneous third- and fourth-order cumulant diagonalization. IEEE Trans. Signal Process. 52 (5) (2004)
Laurenz Wiskott
Slow Feature Analysis: A Theoretical Analysis of Optimal Free Responses. Neural Comput. 15 (9) (2003)
Pietro Berkes, Laurenz Wiskott
Applying Slow Feature Analysis to Image Sequences Yields a Rich Repertoire of Complex Cell Properties. ICANN (2002)
Tobias Blaschke, Laurenz Wiskott
An Improved Cumulant Based Method for Independent Component Analysis. ICANN (2002)
Laurenz Wiskott, Terrence J. Sejnowski
Slow Feature Analysis: Unsupervised Learning of Invariances. Neural Comput. 14 (4) (2002)
Laurenz Wiskott
Segmentation from motion: combining Gabor- and Mallat-wavelets to overcome the aperture and correspondence problems. Pattern Recognit. 32 (10) (1999)
Laurenz Wiskott
The role of topographical constraints in face recognition. Pattern Recognit. Lett. 20 (1) (1999)
Laurenz Wiskott
Learning invariance manifolds. Neurocomputing (1999)
Laurenz Wiskott, Terrence J. Sejnowski
Constrained Optimization for Neural Map Formation: A Unifying Framework for Weight Growth and Normalization. Neural Comput. 10 (3) (1998)

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Publication Activity (10 Years)

Top Topics

Top Venues

Laurenz Wiskott