Jonas Rothfuss

According to our database, Jonas Rothfuss authored at least 23 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Data-Efficient Task Generalization via Probabilistic Model-Based Meta Reinforcement Learning.

Arjun Bhardwaj, Jonas Rothfuss, Bhavya Sukhija, Yarden As, Marco Hutter, Stelian Coros, Andreas Krause

IEEE Robotics Autom. Lett., 2024

Bridging the Sim-to-Real Gap with Bayesian Inference.

Jonas Rothfuss, Bhavya Sukhija, Lenart Treven, Florian Dörfler, Stelian Coros, Andreas Krause

CoRR, 2024

2023

Lifelong bandit optimization: no prior and no regret.

Felix Schur, Parnian Kassraie, Jonas Rothfuss, Andreas Krause

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Hallucinated adversarial control for conservative offline policy evaluation.

Jonas Rothfuss, Bhavya Sukhija, Tobias Birchler, Parnian Kassraie, Andreas Krause

Proceedings of the Uncertainty in Artificial Intelligence, 2023

MARS: Meta-learning as Score Matching in the Function Space.

Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause

Proceedings of the Eleventh International Conference on Learning Representations, 2023

BaCaDI: Bayesian Causal Discovery with Unknown Interventions.

Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

PAC-Bayesian Meta-Learning: From Theory to Practice.

Jonas Rothfuss, Martin Josifoski, Vincent Fortuin, Andreas Krause

CoRR, 2022

Instance-Dependent Generalization Bounds via Optimal Transport.

Songyan Hou, Parnian Kassraie, Anastasis Kratsios, Jonas Rothfuss, Andreas Krause

CoRR, 2022

Amortized Inference for Causal Structure Learning.

Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Meta-Learning Hypothesis Spaces for Sequential Decision-making.

Parnian Kassraie, Jonas Rothfuss, Andreas Krause

Proceedings of the International Conference on Machine Learning, 2022

Meta-Learning Priors for Safe Bayesian Optimization.

Jonas Rothfuss, Christopher König, Alisa Rupenyan, Andreas Krause

Proceedings of the Conference on Robot Learning, 2022

2021

Variational Causal Networks: Approximate Bayesian Inference over Causal Structures.

Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer

CoRR, 2021

Robustness to Pruning Predicts Generalization in Deep Neural Networks.

Lorenz Kuhn, Clare Lyle, Aidan N. Gomez, Jonas Rothfuss, Yarin Gal

CoRR, 2021

Meta-Learning Reliable Priors in the Function Space.

Jonas Rothfuss, Dominique Heyn, Jinfan Chen, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

DiBS: Differentiable Bayesian Structure Learning.

Lars Lorch, Jonas Rothfuss, Bernhard Schölkopf, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees.

Jonas Rothfuss, Vincent Fortuin, Martin Josifoski, Andreas Krause

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees.

Jonas Rothfuss, Vincent Fortuin, Andreas Krause

CoRR, 2020

2019

Noise Regularization for Conditional Density Estimation.

Jonas Rothfuss, Fábio Ferreira, Simon Boehm, Simon Walther, Maxim Ulrich, Tamim Asfour, Andreas Krause

CoRR, 2019

Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks.

Jonas Rothfuss, Fábio Ferreira, Simon Walther, Maxim Ulrich

CoRR, 2019

ProMP: Proximal Meta-Policy Search.

Jonas Rothfuss, Dennis Lee, Ignasi Clavera, Tamim Asfour, Pieter Abbeel

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Deep Episodic Memory: Encoding, Recalling, and Predicting Episodic Experiences for Robot Action Execution.

Jonas Rothfuss, Fábio Ferreira, Eren Erdal Aksoy, You Zhou, Tamim Asfour

IEEE Robotics Autom. Lett., 2018

Introducing the Simulated Flying Shapes and Simulated Planar Manipulator Datasets.

Fábio Ferreira, Jonas Rothfuss, Eren Erdal Aksoy, You Zhou, Tamim Asfour

CoRR, 2018

Model-Based Reinforcement Learning via Meta-Policy Optimization.

Ignasi Clavera, Jonas Rothfuss, John Schulman, Yasuhiro Fujita, Tamim Asfour, Pieter Abbeel

Proceedings of the 2nd Annual Conference on Robot Learning, 2018