Seneviratne, Martin

3 publications

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

NeurIPSW 2021 BEDS-Bench: Behavior of EHR-Models Under Distributional Shift - A Benchmark Anand Avati, Martin Seneviratne, Yuan Xue, Zhen Xu, Balaji Lakshminarayanan, Andrew M. Dai

NeurIPS 2020 Learning to Select Best Forecast Tasks for Clinical Outcome Prediction Yuan Xue, Nan Du, Anne Mottram, Martin Seneviratne, Andrew M Dai