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ORCIDWengong Jin
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2020 – today
- 2024
[j4]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): 177-185 (2024)- [c17]Divya Nori, Wengong Jin:
RNAFlow: RNA Structure & Sequence Design via Inverse Folding-Based Flow Matching. ICML 2024 - [c16]Zhenqiao Song, Tinglin Huang, Lei Li, Wengong Jin:
SurfPro: Functional Protein Design Based on Continuous Surface. ICML 2024 - [c15]Zhenqiao Song, Yunlong Zhao, Wenxian Shi, Wengong Jin, Yang Yang, Lei Li:
Generative Enzyme Design Guided by Functionally Important Sites and Small-Molecule Substrates. ICML 2024 - [i20]Zhenqiao Song, Tinglin Huang, Lei Li, Wengong Jin:
SurfPro: Functional Protein Design Based on Continuous Surface. CoRR abs/2405.06693 (2024) - [i19]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 abs/2405.08205 (2024) - [i18]Divya Nori, Wengong Jin:
RNAFlow: RNA Structure & Sequence Design via Inverse Folding-Based Flow Matching. CoRR abs/2405.18768 (2024) - 2023
- [c14]Minkai Xu, Meng Liu, Wengong Jin, Shuiwang Ji, Jure Leskovec, Stefano Ermon:
Graph and Geometry Generative Modeling for Drug Discovery. KDD 2023: 5833-5834 - [c13]Wengong Jin, Siranush Sarkizova, Xun Chen, Nir Hacohen, Caroline Uhler:
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation. NeurIPS 2023 - [i17]Wengong Jin, Siranush Sarkizova, Xun Chen, Nir Hacohen, Caroline Uhler:
Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation. CoRR abs/2301.10814 (2023) - 2022
- [c12]Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola:
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design. ICLR 2022 - [c11]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Antibody-Antigen Docking and Design via Hierarchical Structure Refinement. ICML 2022: 10217-10227 - [i16]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Antibody-Antigen Docking and Design via Hierarchical Equivariant Refinement. CoRR abs/2207.06616 (2022) - 2021
- [b1]Wengong Jin:
Graph Representation Learning for Drug Discovery. Massachusetts Institute of Technology, USA, 2021 - [j3]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): e2105070118 (2021) - [c10]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: 6688-6698 - [i15]Wengong Jin, Jeremy Wohlwend, Regina Barzilay, Tommi S. Jaakkola:
Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design. CoRR abs/2110.04624 (2021) - 2020
- [c9]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Hierarchical Generation of Molecular Graphs using Structural Motifs. ICML 2020: 4839-4848 - [c8]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Multi-Objective Molecule Generation using Interpretable Substructures. ICML 2020: 4849-4859 - [c7]Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi S. Jaakkola:
Improving Molecular Design by Stochastic Iterative Target Augmentation. ICML 2020: 10716-10726 - [i14]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Hierarchical Generation of Molecular Graphs using Structural Motifs. CoRR abs/2002.03230 (2020) - [i13]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Composing Molecules with Multiple Property Constraints. CoRR abs/2002.03244 (2020) - [i12]Kevin Yang, Wengong Jin, Kyle Swanson, Regina Barzilay, Tommi S. Jaakkola:
Improving Molecular Design by Stochastic Iterative Target Augmentation. CoRR abs/2002.04720 (2020) - [i11]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Adaptive Invariance for Molecule Property Prediction. CoRR abs/2005.03004 (2020) - [i10]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Domain Extrapolation via Regret Minimization. CoRR abs/2006.03908 (2020) - [i9]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 abs/2006.08532 (2020) - [i8]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Discovering Synergistic Drug Combinations for COVID with Biological Bottleneck Models. CoRR abs/2011.04651 (2020)
2010 – 2019
- 2019
- [j2]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): 3370-3388 (2019) - [j1]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): 5304-5305 (2019) - [c6]Wengong Jin, Kevin Yang, Regina Barzilay, Tommi S. Jaakkola:
Learning Multimodal Graph-to-Graph Translation for Molecule Optimization. ICLR (Poster) 2019 - [c5]Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola:
Functional Transparency for Structured Data: a Game-Theoretic Approach. ICML 2019: 3723-3733 - [i7]Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola:
Functional Transparency for Structured Data: a Game-Theoretic Approach. CoRR abs/1902.09737 (2019) - [i6]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 abs/1904.01561 (2019) - [i5]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Multi-resolution Autoregressive Graph-to-Graph Translation for Molecules. CoRR abs/1907.11223 (2019) - 2018
- [c4]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Junction Tree Variational Autoencoder for Molecular Graph Generation. ICML 2018: 2328-2337 - [i4]Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Junction Tree Variational Autoencoder for Molecular Graph Generation. CoRR abs/1802.04364 (2018) - [i3]Wengong Jin, Kevin Yang, Regina Barzilay, Tommi S. Jaakkola:
Learning Multimodal Graph-to-Graph Translation for Molecular Optimization. CoRR abs/1812.01070 (2018) - 2017
- [c3]Tao Lei, Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Deriving Neural Architectures from Sequence and Graph Kernels. ICML 2017: 2024-2033 - [c2]Wengong Jin, Connor W. Coley, Regina Barzilay, Tommi S. Jaakkola:
Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network. NIPS 2017: 2607-2616 - [i2]Tao Lei, Wengong Jin, Regina Barzilay, Tommi S. Jaakkola:
Deriving Neural Architectures from Sequence and Graph Kernels. CoRR abs/1705.09037 (2017) - [i1]Wengong Jin, Connor W. Coley, Regina Barzilay, Tommi S. Jaakkola:
Predicting Organic Reaction Outcomes with Weisfeiler-Lehman Network. CoRR abs/1709.04555 (2017) - 2015
- [c1]Wengong Jin, Tianxing He, Yanmin Qian, Kai Yu:
Paragraph vector based topic model for language model adaptation. INTERSPEECH 2015: 3516-3520
Coauthor Index
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