( events)   Timezone: »  
The 2020 schedule is still incomplete Program Highlights »
Workshop
Sat Dec 12 05:30 AM -- 01:00 PM (PST)
Machine Learning for Molecules
José Miguel Hernández-Lobato · Matt Kusner · Brooks Paige · Marwin Segler · Jennifer Wei





Workshop Home Page

Discovering new molecules and materials is a central pillar of human well-being, providing new medicines, securing the world’s food supply via agrochemicals, or delivering new battery or solar panel materials to mitigate climate change. However, the discovery of new molecules for an application can often take up to a decade, with costs spiraling. Machine learning can help to accelerate the discovery process. The goal of this workshop is to bring together researchers interested in improving applications of machine learning for chemical and physical problems and industry experts with practical experience in pharmaceutical and agricultural development. In a highly interactive format, we will outline the current frontiers and present emerging research directions. We aim to use this workshop as an opportunity to establish a common language between all communities, to actively discuss new research problems, and also to collect datasets by which novel machine learning models can be benchmarked. The program is a collection of invited talks, alongside contributed posters. A panel discussion will provide different perspectives and experiences of influential researchers from both fields and also engage open participant conversation. An expected outcome of this workshop is the interdisciplinary exchange of ideas and initiation of collaboration.

Opening Remarks
Speaker Introduction: Nadine Schneider (Speaker Introduction)
Invited Talk: Nadine Schneider (Talk)
Nadine Schneider
Invited Talk: Nadine Schneider - Live Q&A (Q&A)
Speaker Introduction: Frank Noe (Speaker Introduction)
Invited Talk: Frank Noe (Talk)
Frank Noe
Invited Talk: Frank Noe - Live Q&A (Q&A)
Contributed Talk: Evidential Deep Learning for Guided Molecular Property Prediction and Discovery - Ava Soleimany, Alexander Amini, Samuel Goldman, Daniela Rus, Sangeeta Bhatia and Connor Coley (Talk)
Ava P Soleimany
Contributed Talk: Gaussian Process Molecular Property Prediction with FlowMO - Henry Moss and Ryan-Rhys Griffiths (Talk)
Henry Moss
Contributed Talk: Explaining Deep Graph Networks with Molecular Counterfactuals - Davide Bacciu and Danilo Numeroso (Talk)
Danilo Numeroso
Speaker Introduction: Klaus Robert-Müller (Speaker Introduction)
Invited Talk: Klaus Robert-Müller (Talk)
Klaus-Robert Müller
Invited Talk: Klaus Robert-Müller - Live Q&A (Q&A)
Speaker Introduction: Rocio Mercado (Speaker Introduction)
Invited Talk: Rocio Mercado (Talk)
Rocío Mercado
Invited Talk: Rocio Mercado - Live Q&A (Q&A)
Spotlight Talk: Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction - Agnieszka Pocha, Tomasz Danel and Lukasz Maziarka (Talk)
Tomasz Danel
Spotlight Talk: Completion of partial reaction equations - Alain C. Vaucher, Philippe Schwaller and Teodoro Laino (Talk)
Alain Vaucher,
Spotlight Talk: Molecular representation learning with language models and domain-relevant auxiliary tasks - Benedek Fabian, Thomas Edlich, Héléna Gaspar, Marwin Segler, Joshua Meyers, Marco Fiscato and Mohamed Ahmed (Talk)
Benedek Fabian
Spotlight Talk: Accelerate the screening of complex materials by learning to reduce random and systematic errors - Tian Xie, Yang Shao-Horn and Jeffrey Grossman. (Talk)
Tian Xie
Break
Panel (Discussion Panel)
Contributed Talk: Bayesian GNNs for Molecular Property Prediction - George Lamb and Brooks Paige (Talk)
William Lamb
Contributed Talk: Design of Experiments for Verifying Biomolecular Networks - Ruby Sedgwick, John Goertz, Ruth Misener, Molly Stevens and Mark van der Wilk. (Talk)
Ruby Sedgwick
Contributed Talk: Multi-task learning for electronic structure to predict and explore molecular potential -Zhuoran Qiao, Feizhi Ding, Matthew Welborn, Peter J. Bygrave, Daniel G. A. Smith, Animashree Anandkumar, Frederick R. Manby and Thomas F. Miller III (Talk)
Zhuoran Qiao
Speaker Introduction: Patrick Walters (Speaker Introduction)
Invited Talk: Patrick Walters (Talk)
Patrick Walters
Invited Talk: Patrick Walters - Live Q&A (Q&A)
Speaker Introduction: Yannick Djoumbou Feunang (Speaker Introduction)
Invited Talk: Yannick Djoumbou Feunang (Talk)
Yannick Djoumbou Feunang
Invited Talk: Yannick Djoumbou Feunang - Live Q&A (Q&A)
Spotlight Talk: Data augmentation strategies to improve reaction yield predictions and estimate uncertainty - Philippe Schwaller, Alain Vaucher, Teodoro Laino and Jean-Louis Reymond (Talk)
Philippe Schwaller
Spotlight Talk: Message Passing Networks for Molecules with Tetrahedral Chirality - Lagnajit Pattanaik, Octavian Ganea, Ian Coley, Klavs Jensen, William Green and Connor Coley. (Talk)
Lagnajit Pattanaik
Spotlight Talk: Protein model quality assessment using rotation-equivariant, hierarchical neural networks - Stephan Eismann, Patricia Suriana, Bowen Jing, Raphael Townshend and Ron Dror. (Talk)
Stephan Eismann
Spotlight Talk: Crystal Structure Search with Random Relaxations Using Graph Networks - Gowoon Cheon, Lusann Yang, Kevin McCloskey, Evan Reed and Ekin Cubuk (Talk)
Gowoon Cheon
Speaker Introduction: Benjamin Sanchez-Lengeling (Speaker Introduction)
Invited Talk: Benjamin Sanchez-Lengeling (Talk)
Benjamin Sanchez-Lengeling
Invited Talk: Benjamin Sanchez-Lengeling - Live Q&A (Q&A)
Speaker Introduction: Jennifer Listgarten (Speaker Introduction)
Invited Talk: Jennifer Listgarten (Talk)
Jennifer Listgarten
Invited Talk: Jennifer Listgarten - Live Q&A (Q&A)
Closing Remarks