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Found 3 papers, 1 papers with code
Individual Fairness under Uncertainty
Algorithmic fairness, the research field of making machine learning (ML) algorithms fair, is an established area in ML.
ESPRIT: Explaining Solutions to Physical Reasoning Tasks
Our framework learns to generate explanations of how the physical simulation will causally evolve so that an agent or a human can easily reason about a solution using those interpretable descriptions.
Multiplicative Forests for Continuous-Time Processes
Learning temporal dependencies between variables over continuous time is an important and challenging task.
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