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03/02/2023
Hallucinated Adversarial Control for Conservative Offline Policy Evaluation
We study the problem of conservative off-policy evaluation (COPE) where ...
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11/14/2022
PAC-Bayesian Meta-Learning: From Theory to Practice
Meta-Learning aims to accelerate the learning on new tasks by acquiring ...
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11/02/2022
Instance-Dependent Generalization Bounds via Optimal Transport
Existing generalization bounds fail to explain crucial factors that driv...
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10/27/2022
Lifelong Bandit Optimization: No Prior and No Regret
In practical applications, machine learning algorithms are often repeate...
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10/24/2022
MARS: Meta-Learning as Score Matching in the Function Space
Meta-learning aims to extract useful inductive biases from a set of rela...
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10/03/2022
Meta-Learning Priors for Safe Bayesian Optimization
In robotics, optimizing controller parameters under safety constraints i...
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06/03/2022
BaCaDI: Bayesian Causal Discovery with Unknown Interventions
Learning causal structures from observation and experimentation is a cen...
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05/25/2022
Amortized Inference for Causal Structure Learning
Learning causal structure poses a combinatorial search problem that typi...
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02/01/2022
Meta-Learning Hypothesis Spaces for Sequential Decision-making
Obtaining reliable, adaptive confidence sets for prediction functions (h...
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06/14/2021
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures
Learning the causal structure that underlies data is a crucial step towa...
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06/06/2021
Meta-Learning Reliable Priors in the Function Space
Meta-Learning promises to enable more data-efficient inference by harnes...
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05/25/2021
DiBS: Differentiable Bayesian Structure Learning
Bayesian structure learning allows inferring Bayesian network structure ...
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03/10/2021
Robustness to Pruning Predicts Generalization in Deep Neural Networks
Existing generalization measures that aim to capture a model's simplicit...
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02/13/2020
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees
Meta-learning can successfully acquire useful inductive biases from data...
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07/21/2019
Noise Regularization for Conditional Density Estimation
Modelling statistical relationships beyond the conditional mean is cruci...
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03/03/2019
Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks
Given a set of empirical observations, conditional density estimation ai...
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10/16/2018
ProMP: Proximal Meta-Policy Search
Credit assignment in Meta-reinforcement learning (Meta-RL) is still poor...
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09/14/2018
Model-Based Reinforcement Learning via Meta-Policy Optimization
Model-based reinforcement learning approaches carry the promise of being...
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07/02/2018
Introducing the Simulated Flying Shapes and Simulated Planar Manipulator Datasets
We release two artificial datasets, Simulated Flying Shapes and Simulate...
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01/12/2018
