Bowen Jing

This page is a disambiguation page, it actually contains mutiple papers from persons of the same or a similar name.

Known people with the same name:

Bibliography

2025
A two-stage dual-task learning strategy for early prediction of pathological complete response to neoadjuvant chemotherapy for breast cancer using dynamic contrast-enhanced magnetic resonance images.
CoRR, February, 2025

The effects of a self-developed virtual reality environment on college EFL learners' vocabulary learning.
Interact. Learn. Environ., January, 2025

ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
Verlet Flows: Exact-Likelihood Integrators for Flow-Based Generative Models.
CoRR, 2024

Generative Modeling of Molecular Dynamics Trajectories.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Dirichlet Flow Matching with Applications to DNA Sequence Design.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Harmonic Self-Conditioned Flow Matching for joint Multi-Ligand Docking and Binding Site Design.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

AlphaFold Meets Flow Matching for Generating Protein Ensembles.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design.
CoRR, 2023

nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance.
CoRR, 2023

EigenFold: Generative Protein Structure Prediction with Diffusion Models.
CoRR, 2023

DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Torsional Diffusion for Molecular Conformer Generation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Subspace Diffusion Generative Models.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Equivariant Graph Neural Networks for 3D Macromolecular Structure.
CoRR, 2021

ATOM3D: Tasks on Molecules in Three Dimensions.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Learning from Protein Structure with Geometric Vector Perceptrons.
Proceedings of the 9th International Conference on Learning Representations, 2021

Rotation-Invariant Gait Identification with Quaternion Convolutional Neural Networks (Student Abstract).
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Protein model quality assessment using rotation-equivariant, hierarchical neural networks.
CoRR, 2020

Rotation-Invariant Gait Identification with Quaternion Convolutional Neural Networks.
CoRR, 2020

Hierarchical, rotation-equivariant neural networks to predict the structure of protein complexes.
CoRR, 2020

2019
SGVAE: Sequential Graph Variational Autoencoder.
CoRR, 2019

Modeling Sensorimotor Coordination as Multi-Agent Reinforcement Learning with Differentiable Communication.
CoRR, 2019


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