Nathan Ng

According to our database, Nathan Ng authored at least 19 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Improving Black-box Robustness with In-Context Rewriting.

Kyle O'Brien, Nathan Ng, Isha Puri, Jorge Mendez, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi, Thomas Hartvigsen

CoRR, 2024

2023

Blind Biological Sequence Denoising with Self-Supervised Set Learning.

Nathan Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho

CoRR, 2023

Unlocking Efficiency: Understanding End-to-End Performance in Distributed Analytics Pipelines.

Abel Souza, Nathan Ng, Tarek F. Abdelzaher, Don Towsley, Prashant J. Shenoy

Proceedings of the IEEE Military Communications Conference, 2023

2022

Tuning the Tail Latency of Distributed Queries Using Replication.

Nathan Ng, Hung Le, Marco Serafini

CoRR, 2022

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

Nathan Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi

CoRR, 2022

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

Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger B. Grosse

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

2021

A Novel Coupled Reaction-Diffusion System for Explainable Gene Expression Profiling.

Muhamed Wael Farouq, Wadii Boulila, Zain U. Hussain, Asrar Rashid, Moiz Ali Shah, Sajid Hussain, Nathan Ng, Dominic Ng, Haris Hanif, M. Guftar Shaikh, Aziz Sheikh, Amir Hussain

Sensors, 2021

Mobile devices and wearable technology for measuring patient outcomes after surgery: a systematic review.

Stephen R. Knight, Nathan Ng, Athanasios Tsanas, Kenneth A. McLean, Claudia Pagliari, Ewen M. Harrison

npj Digit. Medicine, 2021

Sharper bounds for the Chebyshev function θ (x).

Samuel Broadbent, Habiba Kadiri, Allysa Lumley, Nathan Ng, Kirsten Wilk

Math. Comput., 2021

2020

Improving Dialogue Breakdown Detection with Semi-Supervised Learning.

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.

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.

Kyra Yee, Nathan Ng, Yann N. Dauphin, Michael Auli

CoRR, 2019

Facebook FAIR's WMT19 News Translation Task Submission.

Nathan Ng, Kyra Yee, Alexei Baevski, Myle Ott, Michael Auli, Sergey Edunov

Proceedings of the Fourth Conference on Machine Translation, 2019

fairseq: A Fast, Extensible Toolkit for Sequence Modeling.

Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, Michael Auli

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.

Tingfung Lau, Nathan Ng, Julian Gingold, Nina Desai, Julian J. McAuley, Zachary C. Lipton

Proceedings of the Machine Learning for Healthcare Conference, 2019

FGreat: Focused Graph Query Autocompletion.

Nathan Ng, Peipei Yi, Zhiwei Zhang, Byron Choi, Sourav S. Bhowmick, Jianliang Xu

Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

2018

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

Nathan H. Ng, Julian J. McAuley, Julian Gingold, Nina Desai, Zachary C. Lipton

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

Answering the Why-Not Questions of Graph Query Autocompletion.

Guozhong Li, Nathan Ng, Peipei Yi, Zhiwei Zhang, Byron Choi

Proceedings of the Database Systems for Advanced Applications, 2018

2017

Predicting Surgery Duration with Neural Heteroscedastic Regression.

Nathan H. Ng, Rodney A. Gabriel, Julian J. McAuley, Charles Elkan, Zachary C. Lipton

Proceedings of the Machine Learning for Health Care Conference, 2017