28 citations · 102 across the 9 of their papers we have counts for
5 papers · 1 filter
E3x: -Equivariant Deep Learning Made Easy
Oliver T. Unke, Hartmut Maennel
This work introduces E3x, a software package for building neural networks that are equivariant with respect to the Euclidean group , consisting of translations, rota…
The Impact of Reinitialization on Generalization in Convolutional Neural Networks
Ibrahim Alabdulmohsin, Hartmut Maennel, Daniel Keysers
Recent results suggest that reinitializing a subset of the parameters of a neural network during training can improve generalization, particularly for small training sets. We study…
Deep Learning Through the Lens of Example Difficulty
Robert J. N. Baldock, Hartmut Maennel, Behnam Neyshabur
Existing work on understanding deep learning often employs measures that compress all data-dependent information into a few numbers. In this work, we adopt a perspective based on t…
Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates
Hugo Penedones, Carlos Riquelme, Damien Vincent +5
We consider the core reinforcement-learning problem of on-policy value function approximation from a batch of trajectory data, and focus on various issues of Temporal Difference (T…
Temporal Difference Learning with Neural Networks - Study of the Leakage Propagation Problem
Hugo Penedones, Damien Vincent, Hartmut Maennel +3
Temporal-Difference learning (TD) [Sutton, 1988] with function approximation can converge to solutions that are worse than those obtained by Monte-Carlo regression, even in the sim…