Search Results for author: Nathan Ng

Found 11 papers, 5 papers with code

Blind Biological Sequence Denoising with Self-Supervised Set Learning

no code implementations4 Sep 2023 Nathan Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho

This set embedding represents the "average" of the subreads and can be decoded into a prediction of the clean sequence.


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

2 code implementations12 Sep 2022 Juhan Bae, Nathan Ng, Alston Lo, Marzyeh Ghassemi, Roger Grosse

Influence functions efficiently estimate the effect of removing a single training data point on a model's learned parameters.

Predicting Out-of-Domain Generalization with Neighborhood Invariance

no code implementations5 Jul 2022 Nathan Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi

Developing and deploying machine learning models safely depends on the ability to characterize and compare their abilities to generalize to new environments.

Data Augmentation Domain Generalization +3

Localization dynamics in a centrally coupled system

no code implementations12 Jan 2021 Nathan Ng, Sebastian Wenderoth, Rajagopala Reddy Seelam, Eran Rabani, Hans-Dieter Meyer, Michael Thoss, Michael Kolodrubetz

At longer time scales, we see slow growth of the entanglement, which may arise from dephasing mechanisms in the localized system or long-range interactions mediated by the central degree of freedom.

Disordered Systems and Neural Networks

Improving Dialogue Breakdown Detection with Semi-Supervised Learning

no code implementations30 Oct 2020 Nathan Ng, Marzyeh Ghassemi, Narendran Thangarajan, Jiacheng Pan, Qi Guo

In ablations on DBDC4 data from 2019, our semi-supervised learning methods improve the performance of a baseline BERT model by 2\% accuracy.

Data Augmentation

Simple and Effective Noisy Channel Modeling for Neural Machine Translation

1 code implementation IJCNLP 2019 Kyra Yee, Nathan Ng, Yann N. Dauphin, Michael Auli

Previous work on neural noisy channel modeling relied on latent variable models that incrementally process the source and target sentence.

Machine Translation Translation

Embryo staging with weakly-supervised region selection and dynamically-decoded predictions

no code implementations9 Apr 2019 Tingfung Lau, Nathan Ng, Julian Gingold, Nina Desai, Julian McAuley, Zachary C. Lipton

First, noting that in each image the embryo occupies a small subregion, we jointly train a region proposal network with the downstream classifier to isolate the embryo.

Region Proposal

fairseq: A Fast, Extensible Toolkit for Sequence Modeling

6 code implementations NAACL 2019 Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, Michael Auli

fairseq is an open-source sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling, and other text generation tasks.

Language Modelling Text Generation +1

Predicting Surgery Duration with Neural Heteroscedastic Regression

no code implementations17 Feb 2017 Nathan Ng, Rodney A Gabriel, Julian McAuley, Charles Elkan, Zachary C. Lipton

Scheduling surgeries is a challenging task due to the fundamental uncertainty of the clinical environment, as well as the risks and costs associated with under- and over-booking.

regression Scheduling

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