Predicting Surgery Duration with Neural Heteroscedastic Regression. - Nathan H. Ng; Rodney A. Gabriel; Julian J. McAuley; Charles Elkan; Zachary C. Lipton (MLHC, 2017)

Predicting Embryo Morphokinetics in Videos with Late Fusion Nets & Dynamic Decoders. - Nathan H. Ng; Julian J. McAuley; Julian Gingold; Nina Desai; Zachary C. Lipton (ICLR (Workshop), 2018)

Embryo Staging with Weakly-Supervised Region Selection and Dynamically-Decoded Predictions. - Tingfung Lau; Nathan Ng 001; Julian Gingold; Nina Desai; Julian J. McAuley; Zachary C. Lipton (MLHC, 2019)

fairseq: A Fast, Extensible Toolkit for Sequence Modeling. - Myle Ott; Sergey Edunov; Alexei Baevski; Angela Fan; Sam Gross; Nathan Ng 001; David Grangier; Michael Auli (NAACL-HLT (Demonstrations), 2019)

Facebook FAIR's WMT19 News Translation Task Submission. - Nathan Ng 001; Kyra Yee; Alexei Baevski; Myle Ott; Michael Auli; Sergey Edunov (WMT (2), 2019)

Simple and Effective Noisy Channel Modeling for Neural Machine Translation. - Kyra Yee; Nathan Ng 001; Yann N. Dauphin; Michael Auli (CoRR, 2019)

SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness. - Nathan Ng 001; Kyunghyun Cho; Marzyeh Ghassemi (EMNLP (1), 2020)

Improving Dialogue Breakdown Detection with Semi-Supervised Learning. - Nathan Ng 001; Marzyeh Ghassemi; Narendran Thangarajan; Jiacheng Pan; Qi Guo (CoRR, 2020)

If Influence Functions are the Answer, Then What is the Question? - Juhan Bae; Nathan Ng 001; Alston Lo; Marzyeh Ghassemi; Roger B. Grosse (NeurIPS, 2022)

Predicting Out-of-Domain Generalization with Local Manifold Smoothness. - Nathan Ng 001; Neha Hulkund; Kyunghyun Cho; Marzyeh Ghassemi (CoRR, 2022)

Predicting Out-of-Domain Generalization with Neighborhood Invariance. - Nathan H. Ng; Neha Hulkund; Kyunghyun Cho; Marzyeh Ghassemi (Trans. Mach. Learn. Res., 2023)

Measuring Stochastic Data Complexity with Boltzmann Influence Functions. - Nathan H. Ng; Roger Baker Grosse; Marzyeh Ghassemi (ICML, 2024)

Improving Black-box Robustness with In-Context Rewriting. - Kyle O'Brien; Nathan Ng 001; Isha Puri; Jorge Mendez; Hamid Palangi; Yoon Kim; Marzyeh Ghassemi; Thomas Hartvigsen (CoRR, 2024)

Blind Biological Sequence Denoising with Self-Supervised Set Learning. - Nathan H. Ng; Ji Won Park; Jae Hyeon Lee; Ryan Lewis Kelly; Stephen Ra; Kyunghyun Cho (Trans. Mach. Learn. Res., 2024)

Improving Black-box Robustness with In-Context Rewriting. - Kyle O'Brien; Nathan Hoyen Ng; Isha Puri; Jorge Mendez-Mendez; Hamid Palangi; Yoon Kim; Marzyeh Ghassemi; Thomas Hartvigsen (Trans. Mach. Learn. Res., 2024)

Robustness and Invariance in Neural Networks - Nathan Ng 001 (2024)