Learned optimizers that outperform SGD on wall-clock and test loss. - Luke Metz; Niru Maheswaranathan; Jeremy Nixon; C. Daniel Freeman; Jascha Sohl-Dickstein (CoRR, 2018)

Measuring Calibration in Deep Learning. - Jeremy Nixon; Michael W. Dusenberry; Linchuan Zhang; Ghassen Jerfel; Dustin Tran (CVPR Workshops, 2019)

Understanding and correcting pathologies in the training of learned optimizers. - Luke Metz; Niru Maheswaranathan; Jeremy Nixon; C. Daniel Freeman; Jascha Sohl-Dickstein (ICML, 2019)

Analyzing the role of model uncertainty for electronic health records. - Michael W. Dusenberry; Dustin Tran; Edward Choi; Jonas Kemp; Jeremy Nixon; Ghassen Jerfel; Katherine A. Heller; Andrew M. Dai (CHIL, 2020)

Semi-Supervised Class Discovery. - Jeremy Nixon; Jeremiah Z. Liu; David Berthelot (CoRR, 2020)

Resolving Spurious Correlations in Causal Models of Environments via Interventions. - Sergei Volodin; Nevan Wichers; Jeremy Nixon (CoRR, 2020)

Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. - Zachary Nado; Neil Band; Mark Collier; Josip Djolonga; Michael W. Dusenberry; Sebastian Farquhar; Angelos Filos; Marton Havasi; Rodolphe Jenatton; Ghassen Jerfel; Jeremiah Z. Liu; Zelda Mariet; et al. (CoRR, 2021)

What are you optimizing for? Aligning Recommender Systems with Human Values. - Jonathan Stray; Ivan Vendrov; Jeremy Nixon; Steven Adler; Dylan Hadfield-Menell (CoRR, 2021)

Structure Learning via Mutual Information. - Jeremy Nixon (CoRR, 2024)