D'Amour, Alexander

15 publications

JMLR 2025 Copula-Based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding Jiajing Zheng, Alexander D'Amour, Alexander Franks

ICLR 2024 CLIP the Bias: How Useful Is Balancing Data in Multimodal Learning? Ibrahim Alabdulmohsin, Xiao Wang, Andreas Peter Steiner, Priya Goyal, Alexander D'Amour, Xiaohua Zhai

NeurIPS 2024 Mind the Graph When Balancing Data for Fairness or Robustness Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa

NeurIPS 2023 Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations Qingyao Sun, Kevin P. Murphy, Sayna Ebrahimi, Alexander D'Amour

TMLR 2023 Fairness and Robustness in Anti-Causal Prediction Maggie Makar, Alexander D'Amour

NeurIPSW 2023 Reward Model Aggregation Zihao Wang, Chirag Nagpal, Alexander D'Amour, Victor Veitch, Sanmi Koyejo

NeurIPS 2022 Diagnosing Failures of Fairness Transfer Across Distribution Shift in Real-World Medical Settings Jessica Schrouff, Natalie Harris, Sanmi Koyejo, Ibrahim M Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour

ICMLW 2022 Fairness and Robustness in Anti-Causal Prediction Maggie Makar, Alexander D'Amour

NeurIPSW 2022 Tailored Overlap for Learning Under Distribution Shift David Bruns-Smith, Alexander D'Amour, Avi Feller, Steve Yadlowsky

ICLR 2022 The MultiBERTs: BERT Reproductions for Robustness Analysis Thibault Sellam, Steve Yadlowsky, Ian Tenney, Jason Wei, Naomi Saphra, Alexander D'Amour, Tal Linzen, Jasmijn Bastings, Iulia Raluca Turc, Jacob Eisenstein, Dipanjan Das, Ellie Pavlick

JMLR 2022 Underspecification Presents Challenges for Credibility in Modern Machine Learning Alexander D'Amour, Katherine Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yian Ma, Cory McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley

NeurIPS 2021 Counterfactual Invariance to Spurious Correlations in Text Classification Victor Veitch, Alexander D'Amour, Steve Yadlowsky, Jacob Eisenstein

CVPR 2021 On Robustness and Transferability of Convolutional Neural Networks Josip Djolonga, Jessica Yung, Michael Tschannen, Rob Romijnders, Lucas Beyer, Alexander Kolesnikov, Joan Puigcerver, Matthias Minderer, Alexander D'Amour, Dan Moldovan, Sylvain Gelly, Neil Houlsby, Xiaohua Zhai, Mario Lucic

NeurIPS 2021 SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression Steve Yadlowsky, Taedong Yun, Cory Y McLean, Alexander D'Amour

NeurIPS 2017 Reducing Reparameterization Gradient Variance Andrew Miller, Nicholas Foti, Alexander D'Amour, Ryan P. Adams