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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

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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.

Discord for Q&A (Q&A)
Opening Remarks
Invited Talk: Nadine Schneider -Real-world application of ML in drug discovery (Talk)
Nadine Schneider
Invited Talk: Nadine Schneider - Live Q&A (Q&A)
Invited Talk: Frank Noe - The sampling problem in statistical mechanics and Boltzmann-Generating Flows (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
Invited Talk: Klaus Robert-Müller & Kristof Schütt: Machine Learning meets Quantum Chemistry (Talk)
Klaus-Robert Müller, Kristof Schütt
Invited Talk: Klaus Robert-Müller and Kristof Schütt - Live Q&A (Q&A)
Invited Talk: Rocio Mercado - Applying Graph Neural Networks to Molecular Design (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
Poster Session Break (Break)
Panel (Discussion Panel)
Alan Aspuru-Guzik, Jennifer Listgarten, Klaus-Robert Müller, Nadine Schneider
Contributed Talk: Bayesian GNNs for Molecular Property Prediction - George Lamb and Brooks Paige (Talk)
George 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 energy surfaces - Z. Qiao, F. Ding, M. Welborn, P.J. Bygrave, D.G.A. Smith, A. Anandkumar, F. R. Manby and TF. Miller III (Talk)
Zhuoran Qiao
Invited Talk: Patrick Walters - Challenges and Opportunities for Machine Learning in Drug Discovery (Talk)
Patrick Walters
Invited Talk: Patrick Walters - Live Q&A (Q&A)
Invited Talk: Yannick Djoumbou Feunang - In Silico Prediction and Identification of Metabolites with BioTransformer (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
Invited Talk: Benjamin Sanchez-Lengeling - Evaluating Attribution of Molecules with Graph Neural Networks (Talk)
Benjamin Sanchez-Lengeling
Invited Talk: Benjamin Sanchez-Lengeling - Live Q&A (Q&A)
Invited Talk: Jennifer Listgarten (Talk)
Jennifer Listgarten
Invited Talk: Jennifer Listgarten - Live Q&A (Q&A)
Closing Remarks
Poster Session Part 2 (Break)