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02/11/2023
Sequential Underspecified Instrument Selection for Cause-Effect Estimation
Instrumental variable (IV) methods are used to estimate causal effects i...
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02/08/2023
DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks
Learning the causal structure of observable variables is a central focus...
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02/01/2023
GFlowNets for AI-Driven Scientific Discovery
Tackling the most pressing problems for humanity, such as the climate cr...
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11/22/2022
Monte Carlo Forest Search: UNSAT Solver Synthesis via Reinforcement learning
We introduce Monte Carlo Forest Search (MCFS), an offline algorithm for ...
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06/02/2022
Weakly Supervised Representation Learning with Sparse Perturbations
The theory of representation learning aims to build methods that provabl...
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10/29/2021
Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning
A key goal of unsupervised representation learning is "inverting" a data...
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06/18/2021
The Perils of Learning Before Optimizing
Formulating real-world optimization problems often begins with making pr...
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11/02/2020
Exemplar Guided Active Learning
We consider the problem of wisely using a limited budget to label a smal...
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06/19/2020
Valid Causal Inference with (Some) Invalid Instruments
Instrumental variable methods provide a powerful approach to estimating ...
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03/07/2018
Deep Models of Interactions Across Sets
We use deep learning to model interactions across two or more sets of ob...
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12/30/2016