Search Results for author: Sam Witty

Found 5 papers, 1 papers with code

SBI: A Simulation-Based Test of Identifiability for Bayesian Causal Inference

no code implementations23 Feb 2021 Sam Witty, David Jensen, Vikash Mansinghka

This paper introduces simulation-based identifiability (SBI), a procedure for testing the identifiability of queries in Bayesian causal inference approaches that are implemented as probabilistic programs.

Causal Inference Experimental Design +1

Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models

1 code implementation17 Dec 2020 Brittany Johnson, Jesse Bartola, Rico Angell, Katherine Keith, Sam Witty, Stephen J. Giguere, Yuriy Brun

To address bias in machine learning, data scientists need tools that help them understand the trade-offs between model quality and fairness in their specific data domains.

BIG-bench Machine Learning Fairness

Bayesian causal inference via probabilistic program synthesis

no code implementations30 Oct 2019 Sam Witty, Alexander Lew, David Jensen, Vikash Mansinghka

This approach makes it straightforward to incorporate data from atomic interventions, as well as shift interventions, variance-scaling interventions, and other interventions that modify causal structure.

Causal Inference Probabilistic Programming +1

Measuring and Characterizing Generalization in Deep Reinforcement Learning

no code implementations7 Dec 2018 Sam Witty, Jun Ki Lee, Emma Tosch, Akanksha Atrey, Michael Littman, David Jensen

We re-examine what is meant by generalization in RL, and propose several definitions based on an agent's performance in on-policy, off-policy, and unreachable states.

reinforcement-learning reinforcement Learning +1

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