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PAC-Bayesian Meta-Learning: From Theory to Practice


Nov 14, 2022
Jonas Rothfuss, Martin Josifoski, Vincent Fortuin, Andreas Krause

* 50 pages 

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Instance-Dependent Generalization Bounds via Optimal Transport


Nov 07, 2022
Songyan Hou, Parnian Kassraie, Anastasis Kratsios, Jonas Rothfuss, Andreas Krause

* 50 pages, 7 figures 

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Lifelong Bandit Optimization: No Prior and No Regret


Oct 27, 2022
Felix Schur, Parnian Kassraie, Jonas Rothfuss, Andreas Krause

* 32 pages, 6 figures, preprint 

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


Oct 24, 2022
Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause


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Meta-Learning Priors for Safe Bayesian Optimization


Oct 03, 2022
Jonas Rothfuss, Christopher Koenig, Alisa Rupenyan, Andreas Krause

* Accepted for the Conference on Robot Learning (CoRL) 2022 

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BaCaDI: Bayesian Causal Discovery with Unknown Interventions


Jun 03, 2022
Alexander Hägele, Jonas Rothfuss, Lars Lorch, Vignesh Ram Somnath, Bernhard Schölkopf, Andreas Krause


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Amortized Inference for Causal Structure Learning


May 25, 2022
Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf


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Meta-Learning Hypothesis Spaces for Sequential Decision-making


Feb 01, 2022
Parnian Kassraie, Jonas Rothfuss, Andreas Krause

* 21 pages, 9 figures 

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Variational Causal Networks: Approximate Bayesian Inference over Causal Structures


Jun 14, 2021
Yashas Annadani, Jonas Rothfuss, Alexandre Lacoste, Nino Scherrer, Anirudh Goyal, Yoshua Bengio, Stefan Bauer

* 10 pages, 6 figures 

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Meta-Learning Reliable Priors in the Function Space


Jun 06, 2021
Jonas Rothfuss, Dominique Heyn, Jinfan Chen, Andreas Krause

* 23 pages 

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