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ORCIDJonas Rothfuss
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2020 – today
- 2024
[b1]Jonas Rothfuss:
Meta-Learning Priors from Limited Data: From Theory to Practice. ETH Zurich, Zürich, Switzerland, 2024- [j4]Arjun Bhardwaj
, Jonas Rothfuss, Bhavya Sukhija, Yarden As, Marco Hutter, Stelian Coros, Andreas Krause:
Data-Efficient Task Generalization via Probabilistic Model-Based Meta Reinforcement Learning. IEEE Robotics Autom. Lett. 9(4): 3918-3925 (2024) - [i22]Jonas Rothfuss, Bhavya Sukhija, Lenart Treven, Florian Dörfler, Stelian Coros, Andreas Krause:
Bridging the Sim-to-Real Gap with Bayesian Inference. CoRR abs/2403.16644 (2024) - 2023
- [j3]Songyan Hou, Parnian Kassraie, Anastasis Kratsios, Andreas Krause, Jonas Rothfuss:
Instance-Dependent Generalization Bounds via Optimal Transport. J. Mach. Learn. Res. 24: 349:1-349:51 (2023) - [j2]Jonas Rothfuss, Martin Josifoski, Vincent Fortuin, Andreas Krause:
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice. J. Mach. Learn. Res. 24: 386:1-386:62 (2023) - [c12]Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause:
BaCaDI: Bayesian Causal Discovery with Unknown Interventions. AISTATS 2023: 1411-1436 - [c11]Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause:
MARS: Meta-learning as Score Matching in the Function Space. ICLR 2023 - [c10]Jonas Rothfuss, Bhavya Sukhija, Tobias Birchler, Parnian Kassraie, Andreas Krause:
Hallucinated adversarial control for conservative offline policy evaluation. UAI 2023: 1774-1784 - [c9]Felix Schur, Parnian Kassraie, Jonas Rothfuss, Andreas Krause:
Lifelong bandit optimization: no prior and no regret. UAI 2023: 1847-1857 - [i21]Jonas Rothfuss, Bhavya Sukhija, Tobias Birchler, Parnian Kassraie, Andreas Krause:
Hallucinated Adversarial Control for Conservative Offline Policy Evaluation. CoRR abs/2303.01076 (2023) - [i20]Arjun Bhardwaj, Jonas Rothfuss, Bhavya Sukhija, Yarden As, Marco Hutter, Stelian Coros, Andreas Krause:
Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning. CoRR abs/2311.07558 (2023) - 2022
- [c8]Jonas Rothfuss, Christopher König, Alisa Rupenyan, Andreas Krause:
Meta-Learning Priors for Safe Bayesian Optimization. CoRL 2022: 237-265 - [c7]Parnian Kassraie, Jonas Rothfuss, Andreas Krause:
Meta-Learning Hypothesis Spaces for Sequential Decision-making. ICML 2022: 10802-10824 - [c6]Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf:
Amortized Inference for Causal Structure Learning. NeurIPS 2022 - [i19]Parnian Kassraie, Jonas Rothfuss, Andreas Krause:
Meta-Learning Hypothesis Spaces for Sequential Decision-making. CoRR abs/2202.00602 (2022) - [i18]Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf:
Amortized Inference for Causal Structure Learning. CoRR abs/2205.12934 (2022) - [i17]Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause:
BaCaDI: Bayesian Causal Discovery with Unknown Interventions. CoRR abs/2206.01665 (2022) - [i16]Jonas Rothfuss, Christopher König, Alisa Rupenyan, Andreas Krause:
Meta-Learning Priors for Safe Bayesian Optimization. CoRR abs/2210.00762 (2022) - [i15]Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause:
MARS: Meta-Learning as Score Matching in the Function Space. CoRR abs/2210.13319 (2022) - [i14]Felix Schur, Parnian Kassraie, Jonas Rothfuss, Andreas Krause:
Lifelong Bandit Optimization: No Prior and No Regret. CoRR abs/2210.15513 (2022) - [i13]Songyan Hou, Parnian Kassraie, Anastasis Kratsios, Jonas Rothfuss, Andreas Krause:
Instance-Dependent Generalization Bounds via Optimal Transport. CoRR abs/2211.01258 (2022) - [i12]Jonas Rothfuss, Martin Josifoski, Vincent Fortuin, Andreas Krause:
PAC-Bayesian Meta-Learning: From Theory to Practice. CoRR abs/2211.07206 (2022) - 2021
- [c5]Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause:
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees. ICML 2021: 9116-9126 - [c4]Jonas Rothfuss, Dominique Heyn, Jinfan Chen, Andreas Krause:
Meta-Learning Reliable Priors in the Function Space. NeurIPS 2021: 280-293 - [c3]Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause:
DiBS: Differentiable Bayesian Structure Learning. NeurIPS 2021: 24111-24123 - [i11]Lorenz Kuhn, Clare Lyle, Aidan N. Gomez, Jonas Rothfuss, Yarin Gal:
Robustness to Pruning Predicts Generalization in Deep Neural Networks. CoRR abs/2103.06002 (2021) - [i10]Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause:
DiBS: Differentiable Bayesian Structure Learning. CoRR abs/2105.11839 (2021) - [i9]Jonas Rothfuss, Dominique Heyn, Jinfan Chen, Andreas Krause:
Meta-Learning Reliable Priors in the Function Space. CoRR abs/2106.03195 (2021) - [i8]Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer:
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures. CoRR abs/2106.07635 (2021) - 2020
- [i7]Jonas Rothfuss, Vincent Fortuin, Andreas Krause:
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees. CoRR abs/2002.05551 (2020)
2010 – 2019
- 2019
- [c2]Jonas Rothfuss, Dennis Lee, Ignasi Clavera, Tamim Asfour, Pieter Abbeel:
ProMP: Proximal Meta-Policy Search. ICLR (Poster) 2019 - [i6]Jonas Rothfuss, Fábio Ferreira, Simon Walther, Maxim Ulrich:
Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks. CoRR abs/1903.00954 (2019) - [i5]Jonas Rothfuss, Fábio Ferreira, Simon Boehm, Simon Walther, Maxim Ulrich, Tamim Asfour, Andreas Krause:
Noise Regularization for Conditional Density Estimation. CoRR abs/1907.08982 (2019) - 2018
- [j1]Jonas Rothfuss, Fábio Ferreira, Eren Erdal Aksoy, You Zhou, Tamim Asfour:
Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution. IEEE Robotics Autom. Lett. 3(4): 4007-4014 (2018) - [c1]Ignasi Clavera, Jonas Rothfuss, John Schulman, Yasuhiro Fujita, Tamim Asfour, Pieter Abbeel:
Model-Based Reinforcement Learning via Meta-Policy Optimization. CoRL 2018: 617-629 - [i4]Jonas Rothfuss, Fábio Ferreira, Eren Erdal Aksoy, You Zhou, Tamim Asfour:
Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution. CoRR abs/1801.04134 (2018) - [i3]Fábio Ferreira, Jonas Rothfuss, Eren Erdal Aksoy, You Zhou, Tamim Asfour:
Introducing the Simulated Flying Shapes and Simulated Planar Manipulator Datasets. CoRR abs/1807.00703 (2018) - [i2]Ignasi Clavera, Jonas Rothfuss, John Schulman, Yasuhiro Fujita, Tamim Asfour, Pieter Abbeel:
Model-Based Reinforcement Learning via Meta-Policy Optimization. CoRR abs/1809.05214 (2018) - [i1]Jonas Rothfuss, Dennis Lee, Ignasi Clavera, Tamim Asfour, Pieter Abbeel:
ProMP: Proximal Meta-Policy Search. CoRR abs/1810.06784 (2018)
Coauthor Index
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