Jonas Rothfuss

发表

Model-Based Reinforcement Learning via Meta-Policy Optimization pdf

Tamim Asfour, Pieter Abbeel, John Schulman, 2018, CoRL.

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

Eren Erdal Aksoy, You Zhou, Tamim Asfour, 2018, IEEE Robotics and Automation Letters.

Forward-looking P

Jonas Rothfuss, Fábio Ferreira, M. Ulrich, 2019, SSRN Electronic Journal.

Amortized Inference for Causal Structure Learning

Jonas Rothfuss, B. Scholkopf, A. Krause, 2022, ArXiv.

BaCaDI: Bayesian Causal Discovery with Unknown Interventions

Vignesh Ram Somnath, Jonas Rothfuss, B. Scholkopf, 2022, ArXiv.

Meta-Learning Hypothesis Spaces for Sequential Decision-making

Jonas Rothfuss, A. Krause, Parnian Kassraie, 2022, ICML.

Meta-Learning Priors for Safe Bayesian Optimization

Jonas Rothfuss, A. Krause, A. Rupenyan, 2022, ArXiv.

Amortized Inference for Causal Structure Learning

B. Schölkopf, Jonas Rothfuss, B. Scholkopf, 2022, NeurIPS.

MARS: Meta-Learning as Score Matching in the Function Space

Jonas Rothfuss, A. Krause, Krunoslav Lehman Pavasovic, 2022, ArXiv.

Lifelong Bandit Optimization: No Prior and No Regret

Jonas Rothfuss, A. Krause, Parnian Kassraie, 2022, ArXiv.

Instance-Dependent Generalization Bounds via Optimal Transport

Jonas Rothfuss, A. Krause, Songyan Hou, 2022, ArXiv.

PAC-Bayesian Meta-Learning: From Theory to Practice

Jonas Rothfuss, Martin Josifoski, A. Krause, 2022, ArXiv.

Meta-Learning Priors for Safe Bayesian Optimization

Jonas Rothfuss, A. Krause, A. Rupenyan, 2022, CoRL.

BaCaDI: Bayesian Causal Discovery with Unknown Interventions

Vignesh Ram Somnath, B. Schölkopf, Jonas Rothfuss, 2022, AISTATS.

DiBS: Differentiable Bayesian Structure Learning pdf

Bernhard Scholkopf, Andreas Krause, Lars Lorch, 2021, NeurIPS.

MARS: Meta-Learning as Score Matching in the Function Space

Jonas Rothfuss, A. Krause, Krunoslav Lehman Pavasovic, 2022, ArXiv.

ProMP: Proximal Meta-Policy Search pdf

Tamim Asfour, Pieter Abbeel, Dennis Lee, 2018, ICLR.

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

Fábio Ferreira, Jonas Rothfuss, Simon Walther, 2019, ArXiv.

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

Andreas Krause, Vincent Fortuin, Jonas Rothfuss, 2020, ICML.

Noise Regularization for Conditional Density Estimation pdf

Andreas Krause, Tamim Asfour, Jonas Rothfuss, 2019, ArXiv.

Variational Causal Networks: Approximate Bayesian Inference over Causal Structures pdf

Alexandre Lacoste, Anirudh Goyal, Stefan Bauer, 2021, ArXiv.

Lifelong Bandit Optimization: No Prior and No Regret

Jonas Rothfuss, A. Krause, Parnian Kassraie, 2022, UAI.

Robustness to Pruning Predicts Generalization in Deep Neural Networks pdf

Yarin Gal, Clare Lyle, Aidan N. Gomez, 2021, ArXiv.

Meta-Learning Priors for Safe Bayesian Optimization

Jonas Rothfuss, A. Krause, A. Rupenyan, 2022, CoRL.

Meta-Learning Reliable Priors in the Function Space pdf

Andreas Krause, Jonas Rothfuss, Dominique Heyn, 2021, NeurIPS.

Instance-Dependent Generalization Bounds via Optimal Transport

Jonas Rothfuss, A. Krause, Songyan Hou, 2022, ArXiv.

MARS: Meta-Learning as Score Matching in the Function Space

Jonas Rothfuss, A. Krause, Krunoslav Lehman Pavasovic, 2022, ICLR.

Hallucinated Adversarial Control for Conservative Offline Policy Evaluation

Jonas Rothfuss, A. Krause, Parnian Kassraie, 2023, UAI.

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

Andreas Krause, Vincent Fortuin, Jonas Rothfuss, 2020, ICML.

Amortized Inference for Causal Structure Learning

Jonas Rothfuss, A. Krause, Lars Lorch, 2022, NeurIPS.

Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice

Jonas Rothfuss, Martin Josifoski, A. Krause, 2022, 2211.07206.