activity
20182021
most citedMoCL: Data-driven Molecular Fingerprint via Knowledge-aware Contrastive Learning from Molecular Graph

9 citations · 19 across the 5 of their papers we have counts for

collaborators

5 papers

physics.bio-ph2021★ 9 cited

MoCL: Data-driven Molecular Fingerprint via Knowledge-aware Contrastive Learning from Molecular Graph

Mengying Sun, Jing Xing, Huijun Wang +2

Recent years have seen a rapid growth of utilizing graph neural networks (GNNs) in the biomedical domain for tackling drug-related problems. However, like any other deep architectu…

cs.LG2021★ 2 cited

Learning Deep Neural Networks under Agnostic Corrupted Supervision

Boyang Liu, Mengying Sun, Ding Wang +2

Training deep neural models in the presence of corrupted supervision is challenging as the corrupted data points may significantly impact the generalization performance. To allevia…

cs.LG2020★ 1 cited

Robust Collaborative Learning with Noisy Labels

Mengying Sun, Jing Xing, Bin Chen +1

Learning with curriculum has shown great effectiveness in tasks where the data contains noisy (corrupted) labels, since the curriculum can be used to re-weight or filter out noisy…

cs.LG2018

Subspace Network: Deep Multi-Task Censored Regression for Modeling Neurodegenerative Diseases

Mengying Sun, Inci M. Baytas, Liang Zhan +2

Over the past decade a wide spectrum of machine learning models have been developed to model the neurodegenerative diseases, associating biomarkers, especially non-intrusive neuroi…

cs.LG2018★ 7 cited

Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models

Mengying Sun, Fengyi Tang, Jinfeng Yi +2

The surging availability of electronic medical records (EHR) leads to increased research interests in medical predictive modeling. Recently many deep learning based predicted model…