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Louis Kirsch
Louis Kirsch
The Swiss AI Lab IDSIA
Verified email at idsia.ch - Homepage
Title
Cited by
Cited by
Year
Transfer Learning for Speech Recognition on a Budget
J Kunze, L Kirsch, I Kurenkov, A Krug, J Johannsmeier, S Stober
ACL 2017, 168, 2017
1202017
Improving Generalization in Meta Reinforcement Learning using Learned Objectives
L Kirsch, S van Steenkiste, J Schmidhuber
arXiv preprint arXiv:1910.04098, 2019
712019
Modular Networks: Learning to Decompose Neural Computation
L Kirsch, J Kunze, D Barber
Advances in Neural Information Processing Systems, 2408-2418, 2018
652018
Meta Learning Backpropagation And Improving It
L Kirsch, J Schmidhuber
4th Workshop on Meta-Learning at NeurIPS 2020, 2020
262020
Parameter-based value functions
F Faccio, L Kirsch, J Schmidhuber
arXiv preprint arXiv:2006.09226, 2020
102020
Introducing symmetries to black box meta reinforcement learning
L Kirsch, S Flennerhag, H van Hasselt, A Friesen, J Oh, Y Chen
Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7202-7210, 2022
52022
Gaussian mean field regularizes by limiting learned information
J Kunze, L Kirsch, H Ritter, D Barber
Entropy 21 (8), 758, 2019
22019
Goal-Conditioned Generators of Deep Policies
F Faccio, V Herrmann, A Ramesh, L Kirsch, J Schmidhuber
arXiv preprint arXiv:2207.01570, 2022
12022
Self-Referential Meta Learning
L Kirsch, J Schmidhuber
First Conference on Automated Machine Learning (Late-Breaking Workshop), 2022
12022
Scaling Neural Networks Through Sparsity
L Kirsch
Tech. rep, 2018
12018
Framework for Exploring and Understanding Multivariate Correlations
L Kirsch, N Riekenbrauck, D Thevessen, M Pappik, A Stebner, J Kunze, ...
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2017
12017
Exploring through Random Curiosity with General Value Functions
A Ramesh, L Kirsch, S van Steenkiste, J Schmidhuber
Deep RL Workshop NeurIPS 2021, 2021
2021
Noisy Information Bottlenecks for Generalization
J Kunze, L Kirsch, H Ritter, D Barber
2018
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Articles 1–13