Bowen Jing

ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids. H Stark, B Jing, T Geffner, J Yim, T Jaakkola, A Vahdat, K Kreis. International Conference on Learning Representations, 2025.

Generative Modeling of Molecular Dynamics Trajectories. B Jing, H Stark, T Jaakkola, B Berger. Neural Information Processing Systems, 2024.

AlphaFold Meets Flow Matching for Generating Protein Ensembles. B Jing, B Berger, T Jaakkola. International Conference on Machine Learning, 2024.

Dirichlet Flow Matching with Applications to DNA Sequence Design. H Stark, B Jing, B Berger, R Barzilay, T Jaakkola. International Conference on Machine Learning, 2024

Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design. H Stark, B Jing, R Barzilay, T Jaakkola. International Conference on Machine Learning, 2024

Evolution of highly multimodal Rayleigh-Taylor instabilities. B Cheng, B Jing, P Bradley, J Sauppe, R Roycroft. High Energy Density Physics, 2024

Diffusion models in protein structure and docking. J Yim, H Stark, G Corso, B Jing, R Barizilay, T Jaakkola. WIREs Computational Molecular Science, 2024

Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms. B Jing, T Jaakkola, B Berger. International Conference on Learning Representations, 2024.

Protein Model Quality Assessment Using Rotation-Equivariant Transformations on Point Clouds. S Eismann, P Suriana, B Jing, R Townshend, R Dror. Proteins, 2023; 91: 1089-1096.

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking. G Corso, H Stark, B Jing, R Barzilay, T Jaakkola. International Conference on Learning Representations, 2023.

Torsional Diffusion for Molecular Conformer Generation. B Jing, G Corso, J Chang, R Barzilay, T Jaakkola. Neural Information Processing Systems 2022.

Subspace Diffusion Generative Models. B Jing, G Corso, R Berlinghieri, T Jaakkola. European Conference on Computer Vision 2022.

ATOM3D: Tasks On Molecules in Three Dimensions. R Townshend, M Vogele, P Suriana, A Derry, A Powers, Y Laloudakis, S Balachandar, B Jing, B Anderson, S Eismann, R Kondor, R Altman, R Dror. Neural Information Processing Systems 2021 Track on Datasets and Benchmarks.

Learning from Protein Structure with Geometric Vector Perceptrons. B Jing, S Eismann, P Suriana, R Townshend, R Dror. International Conference on Learning Representations 2021.

Hierarchical, rotation-equivariant neural networks to predict the structure of protein complexes. S Eismann, R Townshend, N Thomas, M Jagota, B Jing, R Dror. Proteins, 2021; 89: 493-501.