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07/05/2022
A Tutorial on the Spectral Theory of Markov Chains
Markov chains are a class of probabilistic models that have achieved wid...
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11/26/2021
A model of semantic completion in generative episodic memory
Many different studies have suggested that episodic memory is a generati...
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11/15/2021
Modular Networks Prevent Catastrophic Interference in Model-Based Multi-Task Reinforcement Learning
In a multi-task reinforcement learning setting, the learner commonly ben...
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05/07/2021
Reward prediction for representation learning and reward shaping
One of the fundamental challenges in reinforcement learning (RL) is the ...
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11/09/2020
Singular Sturm-Liouville Problems with Zero Potential (q=0) and Singular Slow Feature Analysis
A Sturm-Liouville problem (λ wy=(ry')'+qy) is singular if its domain is ...
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09/20/2020
Latent Representation Prediction Networks
Deeply-learned planning methods are often based on learning representati...
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09/18/2019
Laplacian Matrix for Dimensionality Reduction and Clustering
Many problems in machine learning can be expressed by means of a graph w...
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07/03/2019
Measuring the Data Efficiency of Deep Learning Methods
In this paper, we propose a new experimental protocol and use it to benc...
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05/30/2019
A Hippocampus Model for Online One-Shot Storage of Pattern Sequences
We present a computational model based on the CRISP theory (Content Repr...
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05/25/2019
Hebbian-Descent
In this work we propose Hebbian-descent as a biologically plausible lear...
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04/22/2019
Learning gradient-based ICA by neurally estimating mutual information
Several methods of estimating the mutual information of random variables...
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08/27/2018
Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening
This paper proposes Power Slow Feature Analysis, a gradient-based method...
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05/22/2018
Global Navigation Using Predictable and Slow Feature Analysis in Multiroom Environments, Path Planning and Other Control Tasks
Extended Predictable Feature Analysis (PFAx) [Richthofer and Wiskott, 20...
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12/02/2017
PFAx: Predictable Feature Analysis to Perform Control
Predictable Feature Analysis (PFA) (Richthofer, Wiskott, ICMLA 2015) is ...
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01/17/2017
Intrinsically Motivated Acquisition of Modular Slow Features for Humanoids in Continuous and Non-Stationary Environments
A compact information-rich representation of the environment, also calle...
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01/15/2016
Improved graph-based SFA: Information preservation complements the slowness principle
Slow feature analysis (SFA) is an unsupervised-learning algorithm that e...
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09/28/2015
Theoretical Analysis of the Optimal Free Responses of Graph-Based SFA for the Design of Training Graphs
Slow feature analysis (SFA) is an unsupervised learning algorithm that e...
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01/23/2014
Gaussian-binary Restricted Boltzmann Machines on Modeling Natural Image Statistics
We present a theoretical analysis of Gaussian-binary restricted Boltzman...
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12/20/2013
Modeling correlations in spontaneous activity of visual cortex with centered Gaussian-binary deep Boltzmann machines
Spontaneous cortical activity -- the ongoing cortical activities in abse...
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11/11/2013