Wengong Jin

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 37

Top Topics

Iterative Refinement

Monotonicity Property

Image Synthesis

Top Venues

J. Chem. Inf. Model.

Publications

Zhenqiao Song, Tinglin Huang, Lei Li, Wengong Jin
SurfPro: Functional Protein Design Based on Continuous Surface. CoRR (2024)
Zhenqiao Song, Yunlong Zhao, Wenxian Shi, Wengong Jin, Yang Yang, Lei Li
Generative Enzyme Design Guided by Functionally Important Sites and Small-Molecule Substrates. CoRR (2024)
Divya Nori, Wengong Jin
RNAFlow: RNA Structure & Sequence Design via Inverse Folding-Based Flow Matching. CoRR (2024)
Felix Wong, Erica J. Zheng, Jacqueline A. Valeri, Nina M. Donghia, Melis N. Anahtar, Satotaka Omori, Alicia Li, Andres Cubillos-Ruiz, Aarti Krishnan, Wengong Jin, Abigail L. Manson, Jens Friedrichs, Ralf Helbig, Behnoush Hajian, Dawid K. Fiejtek, Florence F. Wagner, Holly H. Soutter, Ashlee M. Earl, Jonathan M. Stokes, Lars D. Renner, James J. Collins
Discovery of a structural class of antibiotics with explainable deep learning. Nat. 626 (7997) (2024)
Wengong Jin, Siranush Sarkizova, Xun Chen, Nir Hacohen, Caroline Uhler
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation. CoRR (2023)
Minkai Xu, Meng Liu, Wengong Jin, Shuiwang Ji, Jure Leskovec, Stefano Ermon
Graph and Geometry Generative Modeling for Drug Discovery. KDD (2023)
Wengong Jin, Siranush Sarkizova, Xun Chen, Nir Hacohen, Caroline Uhler
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation. NeurIPS (2023)
Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design. ICLR (2022)
Wengong Jin, Regina Barzilay, Tommi Jaakkola
Antibody-Antigen Docking and Design via Hierarchical Equivariant Refinement. CoRR (2022)
Wengong Jin, Regina Barzilay, Tommi Jaakkola
Antibody-Antigen Docking and Design via Hierarchical Structure Refinement. ICML (2022)
Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design. CoRR (2021)
Wengong Jin, Jonathan M. Stokes, Richard T. Eastman, Zina Itkin, Alexey V. Zakharov, James J. Collins, Tommi S. Jaakkola, Regina Barzilay
Deep learning identifies synergistic drug combinations for treating COVID-19. Proc. Natl. Acad. Sci. USA 118 (39) (2021)
Karren D. Yang, Samuel Goldman, Wengong Jin, Alex X. Lu, Regina Barzilay, Tommi S. Jaakkola, Caroline Uhler
Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis. CVPR (2021)
Karren D. Yang, Samuel Goldman, Wengong Jin, Alex Lu, Regina Barzilay, Tommi S. Jaakkola, Caroline Uhler
Improved Conditional Flow Models for Molecule to Image Synthesis. CoRR (2020)
Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Multi-Objective Molecule Generation using Interpretable Substructures. ICML (2020)
Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi S. Jaakkola
Improving Molecular Design by Stochastic Iterative Target Augmentation. CoRR (2020)
Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Domain Extrapolation via Regret Minimization. CoRR (2020)
Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Adaptive Invariance for Molecule Property Prediction. CoRR (2020)
Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Composing Molecules with Multiple Property Constraints. CoRR (2020)
Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Discovering Synergistic Drug Combinations for COVID with Biological Bottleneck Models. CoRR (2020)
Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Hierarchical Generation of Molecular Graphs using Structural Motifs. CoRR (2020)
Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Hierarchical Generation of Molecular Graphs using Structural Motifs. ICML (2020)
Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi S. Jaakkola
Improving Molecular Design by Stochastic Iterative Target Augmentation. ICML (2020)
Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Multi-resolution Autoregressive Graph-to-Graph Translation for Molecules. CoRR (2019)
Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola
Functional Transparency for Structured Data: a Game-Theoretic Approach. CoRR (2019)
Kevin Yang, Kyle Swanson, Wengong Jin, Connor W. Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi S. Jaakkola, Klavs F. Jensen, Regina Barzilay
Correction to Analyzing Learned Molecular Representations for Property Prediction. J. Chem. Inf. Model. 59 (12) (2019)
Kevin Yang, Kyle Swanson, Wengong Jin, Connor W. Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi S. Jaakkola, Klavs F. Jensen, Regina Barzilay
Are Learned Molecular Representations Ready For Prime Time? CoRR (2019)
Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola
Functional Transparency for Structured Data: a Game-Theoretic Approach. ICML (2019)
Kevin Yang, Kyle Swanson, Wengong Jin, Connor W. Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi S. Jaakkola, Klavs F. Jensen, Regina Barzilay
Analyzing Learned Molecular Representations for Property Prediction. J. Chem. Inf. Model. 59 (8) (2019)
Wengong Jin, Kevin Yang, Regina Barzilay, Tommi S. Jaakkola
Learning Multimodal Graph-to-Graph Translation for Molecule Optimization. ICLR (Poster) (2019)
Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Junction Tree Variational Autoencoder for Molecular Graph Generation. ICML (2018)
Wengong Jin, Kevin Yang, Regina Barzilay, Tommi S. Jaakkola
Learning Multimodal Graph-to-Graph Translation for Molecular Optimization. CoRR (2018)
Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Junction Tree Variational Autoencoder for Molecular Graph Generation. CoRR (2018)
Wengong Jin, Connor W. Coley, Regina Barzilay, Tommi S. Jaakkola
Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network. CoRR (2017)
Wengong Jin, Connor W. Coley, Regina Barzilay, Tommi S. Jaakkola
Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network. NIPS (2017)
Tao Lei, Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Deriving Neural Architectures from Sequence and Graph Kernels. ICML (2017)
Tao Lei, Wengong Jin, Regina Barzilay, Tommi S. Jaakkola
Deriving Neural Architectures from Sequence and Graph Kernels. CoRR (2017)
Wengong Jin, Tianxing He, Yanmin Qian, Kai Yu
Paragraph vector based topic model for language model adaptation. INTERSPEECH (2015)