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Bowen Jing
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引用次数
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Learning from protein structure with geometric vector perceptrons
B Jing, S Eismann, P Suriana, RJL Townshend, R Dror
Ninth International Conference on Learning Representations (ICLR 2021), 2021
3682021
Diffdock: Diffusion steps, twists, and turns for molecular docking
G Corso, H Stärk, B Jing, R Barzilay, T Jaakkola
Eleventh International Conference on Learning Representations (ICLR 2023), 2022
3252022
Torsional Diffusion for Molecular Conformer Generation
B Jing, G Corso, J Chang, R Barzilay, T Jaakkola
Neural Information Processing Systems 2022, 2022
2022022
ATOM3D: Tasks On Molecules in Three Dimensions
RJL Townshend, M Vögele, P Suriana, A Derry, A Powers, Y Laloudakis, ...
NeurIPS 2021 Track on Datasets and Benchmarks, 2021
1102021
Hierarchical, rotation‐equivariant neural networks to select structural models of protein complexes
S Eismann, RJL Townshend, N Thomas, M Jagota, B Jing, RO Dror
Proteins: Structure, Function, and Bioinformatics 89 (5), 493-501, 2021
70*2021
Equivariant Graph Neural Networks for 3D Macromolecular Structure
B Jing, S Eismann, PN Soni, RO Dror
ICML 2021 Workshop on Computational Biology, 2021
692021
Subspace diffusion generative models
B Jing, G Corso, R Berlinghieri, T Jaakkola
European Conference on Computer Vision 2022, 2022
672022
EigenFold: Generative Protein Structure Prediction with Diffusion Models
B Jing, E Erives, P Pao-Huang, G Corso, B Berger, T Jaakkola
ICLR Machine Learning for Drug Discovery Workshop 2023, 2023
412023
Protein model quality assessment using rotation‐equivariant transformations on point clouds
S Eismann, P Suriana, B Jing, RJL Townshend, RO Dror
Proteins: Structure, Function, and Bioinformatics 91 (8), 1089-1096, 2023
12*2023
AlphaFold Meets Flow Matching for Generating Protein Ensembles
B Jing, B Berger, T Jaakkola
arXiv preprint arXiv:2402.04845, 2024
72024
Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design
H Stärk, B Jing, R Barzilay, T Jaakkola
arXiv preprint arXiv:2310.05764, 2023
7*2023
Dirichlet Flow Matching with Applications to DNA Sequence Design
H Stark, B Jing, C Wang, G Corso, B Berger, R Barzilay, T Jaakkola
arXiv preprint arXiv:2402.05841, 2024
62024
Rotation-invariant gait identification with quaternion convolutional neural networks (student abstract)
B Jing, V Prabhu, A Gu, J Whaley
Proceedings of the AAAI conference on artificial intelligence 35 (18), 15805 …, 2021
32021
SGVAE: Sequential Graph Variational Autoencoder
B Jing, EA Chi, J Tang
arXiv preprint arXiv:1912.07800, 2019
22019
Diffusion models in protein structure and docking
J Yim, H Stärk, G Corso, B Jing, R Barzilay, TS Jaakkola
Wiley Interdisciplinary Reviews: Computational Molecular Science 14 (2), e1711, 2024
12024
Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms
B Jing, T Jaakkola, B Berger
arXiv preprint arXiv:2312.04323, 2023
12023
Scalable Multimer Structure Prediction using Diffusion Models
P Pao-Huang, B Jing, B Berger
NeurIPS 2023 AI for Science Workshop, 2023
12023
Verlet Flows: Exact-Likelihood Integrators for Flow-Based Generative Models
E Erives, B Jing, T Jaakkola
arXiv preprint arXiv:2405.02805, 2024
2024
Structured Diffusion Processes in Deep Generative Models
B Jing
Massachusetts Institute of Technology, 2022
2022
Modeling Sensorimotor Coordination as Multi-Agent Reinforcement Learning with Differentiable Communication
B Jing, W Yin
arXiv preprint arXiv:1909.05815, 2019
2019
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