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11/18/2022
Model-based Causal Bayesian Optimization
How should we intervene on an unknown structural causal model to maximiz...
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06/28/2022
Supervised Training of Conditional Monge Maps
Optimal transport (OT) theory describes general principles to define and...
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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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11/15/2021
Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking
Protein complex formation is a central problem in biology, being involve...
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10/20/2021
Hierarchical Skills for Efficient Exploration
In reinforcement learning, pre-trained low-level skills have the potenti...
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07/07/2021
Neural Contextual Bandits without Regret
Contextual bandits are a rich model for sequential decision making given...
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05/28/2021
Near-Optimal Multi-Perturbation Experimental Design for Causal Structure Learning
Causal structure learning is a key problem in many domains. Causal struc...
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04/16/2021
Overfitting in Bayesian Optimization: an empirical study and early-stopping solution
Bayesian Optimization (BO) is a successful methodology to tune the hyper...
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01/29/2018
Information Directed Sampling and Bandits with Heteroscedastic Noise
In the stochastic bandit problem, the goal is to maximize an unknown fun...
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06/27/2012
