The COVID-19 global pandemic has disrupted nearly all aspects of modern life. This year NeurIPS will host a symposium on COVID-19 to frame challenges and opportunities for the machine learning community and to foster a frank discussion on the role of machine learning. A central focus of this symposium will be clearly outlining key areas where machine learning is and is not likely to make a substantive impact. The one-day event will feature talks from leading epidemiologists, biotech leaders, policy makers, and global health experts. Attendees of this symposium will gain a deeper understanding of the current state of the COVID-19 pandemic, challenges and limitations for current machine learning capabilities, how machine learning is accelerating COVID-19 vaccine development, and possible ways machine learning may aid in the present and future pandemics.
COVID-19 Symposium Day 1
COVID-19 Symposium Day 2

COVID-19 Symposium Day 1

Andrew Beam, Tristan Naumann, Tristan Naumann, Katherine Heller, Elaine Nsoesie

2020-12-08T12:00:00-08:00 - 2020-12-08T16:00:00-08:00
Abstract: The COVID-19 global pandemic has disrupted nearly all aspects of modern life. This year NeurIPS will host a symposium on COVID-19 to frame challenges and opportunities for the machine learning community and to foster a frank discussion on the role of machine learning. A central focus of this symposium will be clearly outlining key areas where machine learning is and is not likely to make a substantive impact. The one-day event will feature talks from leading epidemiologists, biotech leaders, policy makers, and global health experts. Attendees of this symposium will gain a deeper understanding of the current state of the COVID-19 pandemic, challenges and limitations for current machine learning capabilities, how machine learning is accelerating COVID-19 vaccine development, and possible ways machine learning may aid in the present and future pandemics.

Live Video

Chat is not available.

Schedule

2020-12-08T12:00:00-08:00 - 2020-12-08T12:15:00-08:00
Opening remarks
2020-12-08T12:15:00-08:00 - 2020-12-08T12:50:00-08:00
COVID-19: Can we test our way out of this?
Michael Mina
2020-12-08T12:50:00-08:00 - 2020-12-08T13:00:00-08:00
COVID-19: Can we test our way out of this? Q&A
2020-12-08T13:00:00-08:00 - 2020-12-08T13:35:00-08:00
A Journey Through the Disorderly World of Diagnostic and Prognostic Models for COVID-19
Laure Wynants
2020-12-08T13:35:00-08:00 - 2020-12-08T13:45:00-08:00
Wynats Q&A
2020-12-08T13:45:00-08:00 - 2020-12-08T14:20:00-08:00
Mobility network models of COVID-19 explain inequities and inform reopening
Emma Pierson
2020-12-08T14:20:00-08:00 - 2020-12-08T14:30:00-08:00
Emma Pierson Q&A
2020-12-08T14:30:00-08:00 - 2020-12-08T14:04:00-08:00
When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes
Zhaozhi Qian
2020-12-08T14:34:00-08:00 - 2020-12-08T14:38:00-08:00
Modern Hopfield Networks and Attention for Immune Repertoire Classification
Michael Widrich
2020-12-08T14:38:00-08:00 - 2020-12-08T14:42:00-08:00
The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models
Yingxiang Yang
2020-12-08T14:42:00-08:00 - 2020-12-08T14:46:00-08:00
How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?
Sören Mindermann, Mrinank Sharma, Jan Brauner
2020-12-08T14:46:00-08:00 - 2020-12-08T14:50:00-08:00
Interpretable Sequence Learning for Covid-19 Forecasting
Sercan Arik
2020-12-08T14:50:00-08:00 - 2020-12-08T14:54:00-08:00
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
Payel Das
2020-12-08T14:54:00-08:00 - 2020-12-08T14:58:00-08:00
Deep Direct Likelihood Knockoffs
Mukund Sudarshan
2020-12-08T14:58:00-08:00 - 2020-12-08T15:02:00-08:00
Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation
Uchenna Akujuobi

COVID-19 Symposium Day 2

Andrew Beam, Tristan Naumann, Tristan Naumann, Katherine Heller, Elaine Nsoesie

2020-12-09T12:00:00-08:00 - 2020-12-09T16:00:00-08:00
Abstract: The COVID-19 global pandemic has disrupted nearly all aspects of modern life. This year NeurIPS will host a symposium on COVID-19 to frame challenges and opportunities for the machine learning community and to foster a frank discussion on the role of machine learning. A central focus of this symposium will be clearly outlining key areas where machine learning is and is not likely to make a substantive impact. The one-day event will feature talks from leading epidemiologists, biotech leaders, policy makers, and global health experts. Attendees of this symposium will gain a deeper understanding of the current state of the COVID-19 pandemic, challenges and limitations for current machine learning capabilities, how machine learning is accelerating COVID-19 vaccine development, and possible ways machine learning may aid in the present and future pandemics.

Live Video

Chat is not available.

Schedule

2020-12-09T12:00:00-08:00 - 2020-12-09T12:15:00-08:00
Opening remarks for day 2 of COVID-19 Symposium
2020-12-09T12:15:00-08:00 - 2020-12-09T12:50:00-08:00
AI Assisted Tracking of Non-pharmaceutical Interventions Implemented Worldwide for COVID-19
Aisha Walcott-Bryant
2020-12-09T12:50:00-08:00 - 2020-12-09T13:00:00-08:00
Walcott-Bryant Q&A
Aisha Walcott-Bryant
2020-12-09T13:00:00-08:00 - 2020-12-09T13:35:00-08:00
Bayesian nowcasting of COVID-19 regional test results in England
Chris C Holmes
2020-12-09T13:35:00-08:00 - 2020-12-09T13:45:00-08:00
Chris Holmes Q&A
Chris C Holmes
2020-12-09T13:45:00-08:00 - 2020-12-09T14:20:00-08:00
Moderna, Vaccine Science, and a Health Information Revolution
Noubar Afeyan
2020-12-09T14:20:00-08:00 - 2020-12-09T14:30:00-08:00
Break
2020-12-09T14:30:00-08:00 - 2020-12-09T14:34:00-08:00
Transfer Learning with Neural Motif Transformer for Predicting Protein-Protein Interactions Between SARS-CoV-2 and Humans
Jack Lanchantin
2020-12-09T14:34:00-08:00 - 2020-12-09T14:38:00-08:00
Addressing Public Health Literacy Disparities through Machine Learning: A Human in the Loop Augmented Intelligence based Tool for Public Health
Anjana Susarla
2020-12-09T14:38:00-08:00 - 2020-12-09T14:42:00-08:00
Quantifying Uncertainty in Deep Spatiotemporal Forecasting for COVID-19
Yi-An Ma, Rose Yu
2020-12-09T14:42:00-08:00 - 2020-12-09T14:46:00-08:00
Mobility network models of COVID-19 explain inequities and inform reopening
Serina Chang
2020-12-09T14:46:00-08:00 - 2020-12-09T14:50:00-08:00
Unsupervised learning for economic risk evaluation in the context of Covid-19 pandemic
SANTIAGO CORTES
2020-12-09T14:50:00-08:00 - 2020-12-09T14:54:00-08:00
Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds
Erik Drysdale
2020-12-09T14:54:00-08:00 - 2020-12-09T14:58:00-08:00
Using Wearables for Influenza-Like Illness Detection: The importance of design
Bret Nestor
2020-12-09T14:58:00-08:00 - 2020-12-09T15:02:00-08:00
A Bayesian Hierarchical Network for Combining Heterogeneous Data Sources in Medical Diagnoses
Claire Donnat
2020-12-09T15:02:00-08:00 - 2020-12-09T15:06:00-08:00
Designing a Prospective COVID-19 Therapeutic with Reinforcement Learning
Marcin Skwark
2020-12-09T15:06:00-08:00 - 2020-12-09T15:10:00-08:00
Multiscale PHATE Exploration of SARS-CoV-2 Data Reveals Signature of Disease
Manik Kuchroo