2023 Accepted Papers
Paper Title | Paper Authors |
|---|---|
Integrating Machine Learning and Molecular Modeling with Directed Evolution | Azam Hussain, Charles L. Brooks III |
PINDER: The protein interface dataset and resource | Mehmet Akdel, Alexander Goncearenco, Yusuf Adeshina, Daniel Kovtun, David Baugher, David Baugher, Dylan Abramson, Céline Marquet, Tomas Geffner, Zachary Carpenter, Luca Naef, Michael Bronstein |
Molecular Machine Learning for Battery Electrolyte Design | Shang Zhu, Venkatasubramanian Viswanathan |
Substrate Scope Contrastive Loss: Repurposing Human Bias to Learn Representations of Reactive Atoms | Wenhao Gao, Priyanka Raghavan, Ron Shprints, Connor W. Coley |
Generative Marginalization Models | Sulin Liu, Peter J. Ramadge, Ryan P. Adams |
MiniFold: Simple, Fast, Accurate Protein Structure Prediction | Jeremy Wohlwend, Mateo Reveiz, Axel Feldmann, Wengong Jin, Regina Barzilay |
Towards Understanding Generalization for Machine Learning for Mass Spectrometry | Khoo Ling Min Serena, Peter Mikhael, Regina Barzilay |
Conditional Protein Design via Doob’s h-transform | Kieran Didi, Francisco Vargas, Simon Mathis, Vincent Dutordoir, Emile Mathieu, Urszula Julia Komorowska, Pietro Lio |
Using Fragmentation Graphs for Metabolite Annotation | Yan Zhou Chen, Soha Hassoun |
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets | Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michał Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew Fitzgibbon, Błażej Banaszewski, Chad Martin, Dominic Masters |
Evaluating Molecular Graph Representations within Context | Hanchen Wang |
Plausible Baselines for Molecular Conformer Generation | Eric Alcaide, Gengmo Zhou, Ziyao Li |
Accepted Posters
The following table displays the accepted posters and which poster session they will be part of. We will announce accepted posters on Oct. 18, 2023.
Poster Format
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Posters should be sized 48” x 36”, and oriented in landscape.
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All posters should be physically printed. No screens will be available for electronic posters.
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Posters should be printed and brought to the conference on November 8, 2023. Please do not mount your poster on foam core. We will provide push pins for you to affix your poster to the poster board.
Poster Session
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Location. The poster session will take place on the 1st floor of the Koch Institute in the main hallway and in Luria Auditorium.
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Schedule and Map. Board numbers and board assignments will be provided day-of at the Registration Table.
Last updated: Aug. 10, 2023