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01/25/2023
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation
Protein-ligand binding prediction is a fundamental problem in AI-driven ...
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07/14/2022
Antibody-Antigen Docking and Design via Hierarchical Equivariant Refinement
Computational antibody design seeks to automatically create an antibody ...
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10/09/2021
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design
Antibodies are versatile proteins that bind to pathogens like viruses an...
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11/09/2020
Modeling Drug Combinations based on Molecular Structures and Biological Targets
Drug combinations play an important role in therapeutics due to its bett...
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06/15/2020
Improved Conditional Flow Models for Molecule to Image Synthesis
In this paper, we aim to synthesize cell microscopy images under differe...
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06/06/2020
Domain Extrapolation via Regret Minimization
Many real prediction tasks such as molecular property prediction require...
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05/05/2020
Adaptive Invariance for Molecule Property Prediction
Effective property prediction methods can help accelerate the search for...
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02/11/2020
Improving Molecular Design by Stochastic Iterative Target Augmentation
Generative models in molecular design tend to be richly parameterized, d...
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02/08/2020
Composing Molecules with Multiple Property Constraints
Drug discovery aims to find novel compounds with specified chemical prop...
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02/08/2020
Hierarchical Generation of Molecular Graphs using Structural Motifs
Graph generation techniques are increasingly being adopted for drug disc...
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04/02/2019
Are Learned Molecular Representations Ready For Prime Time?
Advancements in neural machinery have led to a wide range of algorithmic...
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02/26/2019
Functional Transparency for Structured Data: a Game-Theoretic Approach
We provide a new approach to training neural models to exhibit transpare...
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12/03/2018
Learning Multimodal Graph-to-Graph Translation for Molecular Optimization
We view molecular optimization as a graph-to-graph translation problem. ...
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02/12/2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
We seek to automate the design of molecules based on specific chemical p...
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09/13/2017
Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network
The prediction of organic reaction outcomes is a fundamental problem in ...
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05/25/2017
