2023 Accepted Papers
Paper Title | Paper Authors |
|---|---|
G2Retro as a two-step graph generative models for retrosynthesis prediction | Ziqi Chen, Oluwatosin R. Ayinde, James R. Fuchs, Huan Sun, Xia Ning |
PepMLM: Target Sequence-Conditioned Generation of Peptide Binders via Masked Language Modeling | Tianlai Chen, Sarah Pertsemlidis, Pranam Chatterjee |
Accessible Molecular Machine Learning Models for the Future of Drug Discovery | Jessica G. Freeze |
Learning from pre-pandemic data for the design and testing of variant-proof vaccines | Sarah Gurev1,2*, Noor Youssef1*, Nicole Thadani1*, Pascal Notin1*, Fadi Ghantous3, Kelly Brock1, Hannah Pierce-Hoffman1, Javier Jaimes4, Ann Dauphine4, Leonid Yurkovetskiy4, Daria Soto4, Ralph Estanboulieh1, Ben Kotzen5, Matteo Bosso4, Jacob Lemieux5, Jeremy Luban4, Mike Seaman3, Debora Marks1,6 |
Data-Centric Learning from Unlabeled Graphs with Diffusion Model | Gang Liu, Meng Jiang |
SE(3) Stochastic Flow Matching for Protein Backbone
Generation | Joey Bose, Tara Akhound-Sadegh, Kilian Fatras, Guillaume Huguet, Jarrid Rector-Brooks, Cheng-Hao Liu, Andrei Cristian Nica, Maksym Korablyov, Michael Bronstein, Alexander Tong |
A graph representation of molecular ensembles for polymer property prediction | Matteo Aldeghi, Connor W. Coley |
Towards equilibrium molecular conformation generation with GFlowNets | Alexandra Volokhova, Michał Koziarski, Alex Hernández-García, Cheng-Hao Liu, Santiago Miret, Pablo Lemos, Luca Thiede, Zichao Yan, Alán Aspuru-Guzik, Yoshua Bengio |
ML Driven Photochemical Synthesis of Helicenes | Lucia Vina-Lopez, Johannes Dietschreit, Simon Axelrod, Aik Rui Tan, Vikas Vashney, Rafael Gomez-Bombarelli |
A Robust, Scalable, and Versatile Approach to Ab Initio Heterogeneous Reconstruction with CryoDRGN-AI | Axel Levy, Frédéric Poitevin, Gordon Wetzstein, Ellen D Zhong |
Triangular Contrastive Learning on Molecular Graphs | MinGyu Choi, Wonseok Shin, Yijingxiu Lu, Sun Kim |
Local, Learned Frames for Molecules | Hannah Lawrence, Saro Passaro, Abhishek Das |
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