Wengong Jin | DeepAI

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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 ...

0 Wengong Jin, et al. ∙

∙ 07/14/2022

Antibody-Antigen Docking and Design via Hierarchical Equivariant Refinement

Computational antibody design seeks to automatically create an antibody ...

12 Wengong Jin, et al. ∙

∙ 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...

0 Wengong Jin, et al. ∙

∙ 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...

9 Wengong Jin, et al. ∙

∙ 06/15/2020

Improved Conditional Flow Models for Molecule to Image Synthesis

In this paper, we aim to synthesize cell microscopy images under differe...

14 Karren Yang, et al. ∙

∙ 06/06/2020

Domain Extrapolation via Regret Minimization

Many real prediction tasks such as molecular property prediction require...

0 Wengong Jin, et al. ∙

∙ 05/05/2020

Adaptive Invariance for Molecule Property Prediction

Effective property prediction methods can help accelerate the search for...

0 Wengong Jin, et al. ∙

∙ 02/11/2020

Improving Molecular Design by Stochastic Iterative Target Augmentation

Generative models in molecular design tend to be richly parameterized, d...

13 Kevin Yang, et al. ∙

∙ 02/08/2020

Composing Molecules with Multiple Property Constraints

Drug discovery aims to find novel compounds with specified chemical prop...

7 Wengong Jin, et al. ∙

∙ 02/08/2020

Hierarchical Generation of Molecular Graphs using Structural Motifs

Graph generation techniques are increasingly being adopted for drug disc...

14 Wengong Jin, et al. ∙

∙ 04/02/2019

Are Learned Molecular Representations Ready For Prime Time?

Advancements in neural machinery have led to a wide range of algorithmic...

0 Kevin Yang, et al. ∙

∙ 02/26/2019

Functional Transparency for Structured Data: a Game-Theoretic Approach

We provide a new approach to training neural models to exhibit transpare...

0 Guang-He Lee, et al. ∙

∙ 12/03/2018

Learning Multimodal Graph-to-Graph Translation for Molecular Optimization

We view molecular optimization as a graph-to-graph translation problem. ...

0 Wengong Jin, et al. ∙

∙ 02/12/2018

Junction Tree Variational Autoencoder for Molecular Graph Generation

We seek to automate the design of molecules based on specific chemical p...

0 Wengong Jin, et al. ∙

∙ 09/13/2017

Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network

The prediction of organic reaction outcomes is a fundamental problem in ...

0 Wengong Jin, et al. ∙

∙ 05/25/2017

Deriving Neural Architectures from Sequence and Graph Kernels

The design of neural architectures for structured objects is typically g...

0 Tao Lei, et al. ∙

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