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
Tue, Dec 8th @ 20:00 GMT – Wed, Dec 9th @ 00:00 GMT
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
Tue, Dec 8th, 2020 @ 20:00 – 20:15 GMT
Opening remarks
Tue, Dec 8th, 2020 @ 20:15 – 20:50 GMT
COVID-19: Can we test our way out of this?
Michael Mina
Tue, Dec 8th, 2020 @ 20:50 – 21:00 GMT
COVID-19: Can we test our way out of this? Q&A
Tue, Dec 8th, 2020 @ 21:00 – 21:35 GMT
A Journey Through the Disorderly World of Diagnostic and Prognostic Models for COVID-19
Laure Wynants
Tue, Dec 8th, 2020 @ 21:35 – 21:45 GMT
Wynats Q&A
Tue, Dec 8th, 2020 @ 21:45 – 22:20 GMT
Mobility network models of COVID-19 explain inequities and inform reopening
Emma Pierson
Tue, Dec 8th, 2020 @ 22:20 – 22:30 GMT
Emma Pierson Q&A
Tue, Dec 8th, 2020 @ 22:30 – 22:04 GMT
When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes
Zhaozhi Qian
Tue, Dec 8th, 2020 @ 22:34 – 22:38 GMT
Modern Hopfield Networks and Attention for Immune Repertoire Classification
Michael Widrich
Tue, Dec 8th, 2020 @ 22:38 – 22:42 GMT
The Devil is in the Detail: A Framework for Macroscopic Prediction via Microscopic Models
Yingxiang Yang
Tue, Dec 8th, 2020 @ 22:42 – 22:46 GMT
How Robust are the Estimated Effects of Nonpharmaceutical Interventions against COVID-19?
Sören Mindermann, Mrinank Sharma, Jan Brauner
Tue, Dec 8th, 2020 @ 22:46 – 22:50 GMT
Interpretable Sequence Learning for Covid-19 Forecasting
Sercan Arik
Tue, Dec 8th, 2020 @ 22:50 – 22:54 GMT
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models
Payel Das
Tue, Dec 8th, 2020 @ 22:54 – 22:58 GMT
Deep Direct Likelihood Knockoffs
Mukund Sudarshan
Tue, Dec 8th, 2020 @ 22:58 – 23:02 GMT
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
Wed, Dec 9th @ 20:00 GMT – Thu, Dec 10th @ 00:00 GMT
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
Wed, Dec 9th, 2020 @ 20:00 – 20:15 GMT
Opening remarks for day 2 of COVID-19 Symposium
Wed, Dec 9th, 2020 @ 20:15 – 20:50 GMT
AI Assisted Tracking of Non-pharmaceutical Interventions Implemented Worldwide for COVID-19
Aisha Walcott-Bryant
Wed, Dec 9th, 2020 @ 20:50 – 21:00 GMT
Walcott-Bryant Q&A
Aisha Walcott-Bryant
Wed, Dec 9th, 2020 @ 21:00 – 21:35 GMT
Bayesian nowcasting of COVID-19 regional test results in England
Chris C Holmes
Wed, Dec 9th, 2020 @ 21:35 – 21:45 GMT
Chris Holmes Q&A
Chris C Holmes
Wed, Dec 9th, 2020 @ 21:45 – 22:20 GMT
Moderna, Vaccine Science, and a Health Information Revolution
Noubar Afeyan
Wed, Dec 9th, 2020 @ 22:20 – 22:30 GMT
Break
Wed, Dec 9th, 2020 @ 22:30 – 22:34 GMT
Transfer Learning with Neural Motif Transformer for Predicting Protein-Protein Interactions Between SARS-CoV-2 and Humans
Jack Lanchantin
Wed, Dec 9th, 2020 @ 22:34 – 22:38 GMT
Addressing Public Health Literacy Disparities through Machine Learning: A Human in the Loop Augmented Intelligence based Tool for Public Health
Anjana Susarla
Wed, Dec 9th, 2020 @ 22:38 – 22:42 GMT
Quantifying Uncertainty in Deep Spatiotemporal Forecasting for COVID-19
Yi-An Ma, Rose Yu
Wed, Dec 9th, 2020 @ 22:42 – 22:46 GMT
Mobility network models of COVID-19 explain inequities and inform reopening
Serina Chang
Wed, Dec 9th, 2020 @ 22:46 – 22:50 GMT
Unsupervised learning for economic risk evaluation in the context of Covid-19 pandemic
SANTIAGO CORTES
Wed, Dec 9th, 2020 @ 22:50 – 22:54 GMT
Forecasting Emergency Department Capacity Constraints for COVID Isolation Beds
Erik Drysdale
Wed, Dec 9th, 2020 @ 22:54 – 22:58 GMT
Using Wearables for Influenza-Like Illness Detection: The importance of design
Bret Nestor
Wed, Dec 9th, 2020 @ 22:58 – 23:02 GMT
A Bayesian Hierarchical Network for Combining Heterogeneous Data Sources in Medical Diagnoses
Claire Donnat
Wed, Dec 9th, 2020 @ 23:02 – 23:06 GMT
Designing a Prospective COVID-19 Therapeutic with Reinforcement Learning
Marcin Skwark
Wed, Dec 9th, 2020 @ 23:06 – 23:10 GMT
Multiscale PHATE Exploration of SARS-CoV-2 Data Reveals Signature of Disease
Manik Kuchroo