Jonas Rothfuss
14 papers · 2018–2023 · 7 venues · across top CS/AI venues
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Research topics
Artificial Intelligence
(13)
Machine Learning
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Learning Paradigms · Artificial Intelligence
(10)
Optimization & Theory
(8)
Core AI
(5)
Bayesian & Probabilistic · Artificial Intelligence
(4)
Deep Learning
(3)
Learning Types
(3)
Reinforcement Learning
(2)
Bayesian & Probabilistic · Machine Learning
(2)
Core Methods
(2)
Learning Paradigms · Machine Learning
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(2)
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(2)
Mathematics & Optimization
(1)
Keywords
neural network
(3)
uncertainty quantification
(3)
causal discovery
(3)
bayesian neural network
(3)
variational inference
(3)
bayesian optimization
(3)
epistemic uncertainty
(2)
bayesian inference
(2)
inductive bia
(2)
stochastic process
(2)
uncertainty estimation
(2)
generalization bound
(2)
sequential decision making
(1)
policy optimization
(1)
gradient-based optimization
(1)
sample efficiency
(1)
causal inference
(1)
gaussian process
(1)
policy gradient
(1)
representation learning
(1)
Papers
BaCaDI: Bayesian Causal Discovery with Unknown Interventions
AISTATS 2023
Hallucinated adversarial control for conservative offline policy evaluation
UAI 2023
Instance-Dependent Generalization Bounds via Optimal Transport
JMLR 2023
Lifelong bandit optimization: no prior and no regret
UAI 2023
MARS: Meta-learning as Score Matching in the Function Space
ICLR 2023
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice
JMLR 2023
Amortized Inference for Causal Structure Learning
NeurIPS 2022
Meta-Learning Hypothesis Spaces for Sequential Decision-making
ICML 2022
Meta-Learning Priors for Safe Bayesian Optimization
CoRL 2022
DiBS: Differentiable Bayesian Structure Learning
NeurIPS 2021
Meta-Learning Reliable Priors in the Function Space
NeurIPS 2021
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
ICML 2021
ProMP: Proximal Meta-Policy Search
ICLR 2019
Model-Based Reinforcement Learning via Meta-Policy Optimization
CoRL 2018