David Madras | DeepAI

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∙ 10/25/2021

Identifying and Benchmarking Natural Out-of-Context Prediction Problems

Deep learning systems frequently fail at out-of-context (OOC) prediction...

3 David Madras, et al. ∙

∙ 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...

58 Robert Adragna, et al. ∙

∙ 06/18/2020

Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

Standard causal discovery methods must fit a new model whenever they enc...

41 Sindy Löwe, et al. ∙

∙ 10/21/2019

Detecting Extrapolation with Local Ensembles

We present local ensembles, a method for detecting extrapolation at test...

0 David Madras, et al. ∙

∙ 09/18/2019

Causal Modeling for Fairness in Dynamical Systems

In this work, we present causal directed acyclic graphs (DAGs) as a unif...

12 Elliot Creager, et al. ∙

∙ 06/06/2019

Flexibly Fair Representation Learning by Disentanglement

We consider the problem of learning representations that achieve group a...

4 Elliot Creager, et al. ∙

∙ 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...

4 David Madras, et al. ∙

∙ 02/17/2018

Learning Adversarially Fair and Transferable Representations

In this work, we advocate for representation learning as the key to miti...

0 David Madras, et al. ∙

∙ 11/17/2017

Predict Responsibly: Increasing Fairness by Learning To Defer

Machine learning systems, which are often used for high-stakes decisions...

0 David Madras, et al. ∙

∙ 10/20/2016

Change-point Detection Methods for Body-Worn Video

Body-worn video (BWV) cameras are increasingly utilized by police depart...

0 Stephanie Allen, et al. ∙

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