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Scalable Solvers Group

Yu-Hang Tang

Yu Hang Tang head
Yu-Hang (Maxin) Tang
Research Scientist, Career-Track
MS #50F-1645
1 Cyclotron Rd
Berkeley, CA 94720 US

 

More details at https://yhtang.github.io/.

Software project:

GraphDot: GPU-accelerated library for graph similarity computation. Repository Documentation Status

Recent presentations:

A High-Throughput Solver for Marginalized Graph Kernels on GPU. IPDPS 2020. slides

Kernel methods for active learning in the chemical space. 2019 DSI Workshop. DOI

 

 

 

 

Journal Articles

Yu-Hang Tang, Wibe A. de Jong, "Prediction of atomization energy using graph kernel and active learning", The Journal of Chemical Physics, January 25, 2019, 150:044107, doi: 10.1063/1.5078640

Yu-Hang Tang, Dongkun Zhang, George Em Karniadakis, "An atomistic fingerprint algorithm for learning ab initio molecular force fields", Journal of Chemical Physics, 2018, 148,

Yu-Hang Tang, Shuhei Kudo, Xin Bian, Zhen Li, George Em Karniadakis, "Multiscale Universal Interface: A concurrent framework for coupling heterogeneous solvers", Journal of Computational Physics, September 15, 2015, 297:13-31, doi: 10.1016/j.jcp.2015.05.004

Conference Papers

Yu-Hang Tang, Oguz Selvitopi, Doru Thom Popovici, Aydın Buluç, "A high-throughput solver for marginalized graph kernels on GPU", IEEE International Parallel and Distributed Processing Symposium (IPDPS), IEEE, May 2020, doi: 10.1109/IPDPS47924.2020.00080