Nathan Ng

Affiliations:

New York University, NY, USA
University of Toronto, ON, Canada (PhD 2024)
Massachusetts Institute of Technology, Cambridge, MA, USA (until 2024)
Facebook AI Research, USA (former)
University of California, San Diego, CA, USA (former)

According to our database¹, Nathan Ng authored at least 16 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Robustness and Invariance in Neural Networks

[BibT_eX]

[DOI]

Nathan Ng

PhD thesis, 2024

Improving Black-box Robustness with In-Context Rewriting.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2024

Blind Biological Sequence Denoising with Self-Supervised Set Learning.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2024

Improving Black-box Robustness with In-Context Rewriting.

[BibT_eX]

[DOI]

CoRR, 2024

Measuring Stochastic Data Complexity with Boltzmann Influence Functions.

[BibT_eX]

[DOI]

Nathan H. Ng

Roger Baker Grosse

Marzyeh Ghassemi

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Predicting Out-of-Domain Generalization with Neighborhood Invariance.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

2022

Predicting Out-of-Domain Generalization with Local Manifold Smoothness.

[BibT_eX]

[DOI]

CoRR, 2022

If Influence Functions are the Answer, Then What is the Question?

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2020

Improving Dialogue Breakdown Detection with Semi-Supervised Learning.

[BibT_eX]

[DOI]

Nathan Ng

Marzyeh Ghassemi

Narendran Thangarajan

Jiacheng Pan

Qi Guo

CoRR, 2020

SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness.

[BibT_eX]

[DOI]

Nathan Ng

Kyunghyun Cho

Marzyeh Ghassemi

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019

Simple and Effective Noisy Channel Modeling for Neural Machine Translation.

[BibT_eX]

[DOI]

CoRR, 2019

Facebook FAIR's WMT19 News Translation Task Submission.

[BibT_eX]

[DOI]

Proceedings of the Fourth Conference on Machine Translation, 2019

fairseq: A Fast, Extensible Toolkit for Sequence Modeling.

[BibT_eX]

[DOI]

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Embryo Staging with Weakly-Supervised Region Selection and Dynamically-Decoded Predictions.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Healthcare Conference, 2019

2018

Predicting Embryo Morphokinetics in Videos with Late Fusion Nets & Dynamic Decoders.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Predicting Surgery Duration with Neural Heteroscedastic Regression.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Health Care Conference, 2017

Nathan Ng

Timeline

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