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04/13/2023
SURFSUP: Learning Fluid Simulation for Novel Surfaces
Modeling the mechanics of fluid in complex scenes is vital to applicatio...
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10/20/2022
MoCoDA: Model-based Counterfactual Data Augmentation
The number of states in a dynamic process is exponential in the number o...
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11/12/2020
Fairness and Robustness in Invariant Learning: A Case Study in Toxicity Classification
Robustness is of central importance in machine learning and has given ri...
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10/14/2020
Exchanging Lessons Between Algorithmic Fairness and Domain Generalization
Standard learning approaches are designed to perform well on average for...
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07/31/2020
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach
Most recommender systems (RS) research assumes that a user's utility can...
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07/06/2020
Counterfactual Data Augmentation using Locally Factored Dynamics
Many dynamic processes, including common scenarios in robotic control an...
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06/14/2020
Is Independence all you need? On the Generalization of Representations Learned from Correlated Data
Despite impressive progress in the last decade, it still remains an open...
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09/18/2019
Causal Modeling for Fairness in Dynamical Systems
In this work, we present causal directed acyclic graphs (DAGs) as a unif...
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06/06/2019
Flexibly Fair Representation Learning by Disentanglement
We consider the problem of learning representations that achieve group a...
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09/07/2018
Fairness Through Causal Awareness: Learning Latent-Variable Models for Biased Data
How do we learn from biased data? Historical datasets often reflect hist...
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07/20/2018
Explaining Image Classifiers by Adaptive Dropout and Generative In-filling
Explanations of black-box classifiers often rely on saliency maps, which...
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02/17/2018
