Zhonglin Cao - RankMe

19 papers A* 2Journal 17

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Fold-CP: A Context Parallelism Framework for Biomolecular Modeling. CoRR Dejun Lin, Simon K. S. Chu, Vishanth Iyer, Youhan Lee, John St. John, Kevin Boyd, Brian Roland, Xiaowei Ren, Guoqing Zhou, Zhonglin Cao, Polina Binder, Yuliya Zhautouskaya, Jakub Zakrzewski, Maximilian Stadler, Kyle Gion, Yuxing Peng, Xi Chen, Tianjing Zhang, Philipp Junk, Michelle Dimon, Pawel Gniewek, Fabian Ortega, McKinley Polen, Ivan Grubisic, Ali Bashir, Graham Holt, Danny Kovtun, Matthias Grass, Luca Naef, Rui Wang, Jian Peng, Anthony B. Costa, Saee Paliwal, Eddie Calleja, Timur Rvachov, Neha Tadimeti, Roy Tal, Emine Küçükbenli
2026	J	`jnl`	Scaling Atomistic Protein Binder Design with Generative Pretraining and Test-Time Compute. CoRR Kieran Didi, Zuobai Zhang, Guoqing Zhou, Danny Reidenbach, Zhonglin Cao, Sooyoung Cha, Tomas Geffner, Christian Dallago, Jian Tang, Michael M. Bronstein, Martin Steinegger, Emine Küçükbenli, Arash Vahdat, Karsten Kreis
2025	J	`jnl`	A Deep-Learning-Based Targeted Interpolation Method for Seismic Data: A Consecutively Missing Trace VSP Case. IEEE Geosci. Remote. Sens. Lett. Wen Yang, Qianggong Song, Le Li, Xiaobin Li, Zhonglin Cao, Pengfei Duan
2025	A*	`conf`	Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow. ICML Zhonglin Cao, Mario Geiger, Allan dos Santos Costa, Danny Reidenbach, Karsten Kreis, Tomas Geffner, Franco Pellegrini, Guoqing Zhou, Emine Küçükbenli
2025	J	`jnl`	Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow. CoRR Zhonglin Cao, Mario Geiger, Allan dos Santos Costa, Danny Reidenbach, Karsten Kreis, Tomas Geffner, Franco Pellegrini, Guoqing Zhou, Emine Küçükbenli
2025	J	`jnl`	La-Proteina: Atomistic Protein Generation via Partially Latent Flow Matching. CoRR Tomas Geffner, Kieran Didi, Zhonglin Cao, Danny Reidenbach, Zuobai Zhang, Christian Dallago, Emine Küçükbenli, Karsten Kreis, Arash Vahdat
2025	A*	`conf`	Proteina: Scaling Flow-based Protein Structure Generative Models. ICLR Tomas Geffner, Kieran Didi, Zuobai Zhang, Danny Reidenbach, Zhonglin Cao, Jason Yim, Mario Geiger, Christian Dallago, Emine Küçükbenli, Arash Vahdat, Karsten Kreis
2025	J	`jnl`	Proteina: Scaling Flow-based Protein Structure Generative Models. CoRR Tomas Geffner, Kieran Didi, Zuobai Zhang, Danny Reidenbach, Zhonglin Cao, Jason Yim, Mario Geiger, Christian Dallago, Emine Küçükbenli, Arash Vahdat, Karsten Kreis
2024	J	`jnl`	BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery. CoRR Peter St. John, Dejun Lin, Polina Binder, Malcolm Greaves, Vega Shah, John St. John, Adrian Lange, Patrick D. Hsu, Rajesh Illango, Arvind Ramanathan, Anima Anandkumar, David H. Brookes, Akosua Busia, Abhishaike Mahajan, Stephen Malina, Neha Prasad, Sam Sinai, Lindsay Edwards, Thomas Gaudelet, Cristian Regep, Martin Steinegger, Burkhard Rost, Alexander Brace, Kyle Hippe, Luca Naef, Keisuke Kamata, George Armstrong, Kevin Boyd, Zhonglin Cao, Han-Yi Chou, Simon Chu, Allan dos Santos Costa, Sajad Darabi, Eric Dawson, Kieran Didi, Cong Fu, Mario Geiger, Michelle Gill, Darren Hsu, Gagan Kaushik, Maria Korshunova, Steven Kothen-Hill, Youhan Lee, Meng Liu, Micha Livne, Zachary McClure, Jonathan Mitchell, Alireza Moradzadeh, Ohad Mosafi, Youssef Nashed, Saee Paliwal, Yuxing Peng, Sara Rabhi, Farhad Ramezanghorbani, Danny Reidenbach, Camir Ricketts, Brian Roland, Kushal Shah, Tyler Shimko, Hassan Sirelkhatim, Savitha Srinivasan, Abraham C. Stern, Dorota Toczydlowska, Srimukh Prasad Veccham, Niccolò Alberto Elia Venanzi, Anton Vorontsov, Jared Wilber, Isabel Wilkinson, Wei Jing Wong, Eva Xue, Cory Ye, Xin Yu, Yang Zhang, Guoqing Zhou, Becca Zandstein, Christian Dallago, Bruno Trentini, Emine Küçükbenli, Timur Rvachov, Eddie Calleja, Johnny Israeli, Harry Clifford, Risto Haukioja, Nicholas Haemel, Kyle Tretina, Neha Tadimeti, Anthony B. Costa
2024	J	`jnl`	EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants. CoRR Allan dos Santos Costa, Ilan Mitnikov, Franco Pellegrini, Ameya Daigavane, Mario Geiger, Zhonglin Cao, Karsten Kreis, Tess E. Smidt, Emine Küçükbenli, Joseph Jacobson
2024	J	`jnl`	Large-Scale Pretraining Improves Sample Efficiency of Active Learning-Based Virtual Screening. J. Chem. Inf. Model. Zhonglin Cao, Simone Sciabola, Ye Wang
2023	J	`jnl`	Large-scale Pretraining Improves Sample Efficiency of Active Learning based Molecule Virtual Screening. CoRR Zhonglin Cao, Simone Sciabola, Ye Wang
2023	J	`jnl`	Neural Network Predicts Ion Concentration Profiles under Nanoconfinement. CoRR Zhonglin Cao, Yuyang Wang, Cooper Lorsung, Amir Barati Farimani
2022	J	`jnl`	MOFormer: Self-Supervised Transformer model for Metal-Organic Framework Property Prediction. CoRR Zhonglin Cao, Rishikesh Magar, Yuyang Wang, Amir Barati Farimani
2022	J	`jnl`	Molecular contrastive learning of representations via graph neural networks. Nat. Mach. Intell. Yuyang Wang, Jianren Wang, Zhonglin Cao, Amir Barati Farimani
2021	J	`jnl`	Deep Reinforcement Learning Optimizes Graphene Nanopores for Efficient Desalination. CoRR Yuyang Wang, Zhonglin Cao, Amir Barati Farimani
2021	J	`jnl`	Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy. Mach. Learn. Sci. Technol. Junwoong Yoon, Zhonglin Cao, Rajesh K. Raju, Yuyang Wang, Robert Burnley, Andrew J. Gellman, Amir Barati Farimani, Zachary W. Ulissi
2021	J	`jnl`	MolCLR: Molecular Contrastive Learning of Representations via Graph Neural Networks. CoRR Yuyang Wang, Jianren Wang, Zhonglin Cao, Amir Barati Farimani
2019	J	`jnl`	Near-Field Communication Sensors. Sensors Zhonglin Cao, Ping Chen, Zhong Ma, Sheng Li, Xingxun Gao, Rui-xin Wu, Lijia Pan, Yi Shi