Tong Wang
Orcid: 0000-0002-9483-0050Affiliations:
- Microsoft Research Asia, Beijing, China
- Tsinghua University, School of Life Sciences, MOE Key Laboratory of Bioinformatics, Beijing, China (PhD 2019)
According to our database1,
Tong Wang
authored at least 19 papers
between 2017 and 2024.
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Bibliography
2024
Miniaturization Design of High-Integration Unmanned Aerial Vehicle-Borne Video Synthetic Aperture Radar Real-Time Imaging Processing Component.
Remote. Sens., April, 2024
An Embedded-GPU-Based Scheme for Real-Time Imaging Processing of Unmanned Aerial Vehicle Borne Video Synthetic Aperture Radar.
Remote. Sens., January, 2024
Overcoming the barrier of orbital-free density functional theory for molecular systems using deep learning.
Nat. Comput. Sci., 2024
Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
2023
DSN-DDI: an accurate and generalized framework for drug-drug interaction prediction by dual-view representation learning.
Briefings Bioinform., January, 2023
M-OFDFT: Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning.
CoRR, 2023
Efficiently incorporating quintuple interactions into geometric deep learning force fields.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
2022
An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022.
CoRR, 2022
Tailoring Molecules for Protein Pockets: a Transformer-based Generative Solution for Structured-based Drug Design.
CoRR, 2022
Briefings Bioinform., 2022
2021
Complementing sequence-derived features with structural information extracted from fragment libraries for protein structure prediction.
BMC Bioinform., 2021
2019
Improved fragment sampling for ab initio protein structure prediction using deep neural networks.
Nat. Mach. Intell., 2019
2018
Identification of residue pairing in interacting β-strands from a predicted residue contact map.
BMC Bioinform., 2018
2017
LRFragLib: an effective algorithm to identify fragments for de novo protein structure prediction.
Bioinform., 2017