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Prediction of Atomization Energy Using Graph Kernel and Active Learning
v1v2v3 (latest)

Prediction of Atomization Energy Using Graph Kernel and Active Learning

16 October 2018
Yu-Hang Tang
W. A. Jong
ArXiv (abs)PDFHTML

Papers citing "Prediction of Atomization Energy Using Graph Kernel and Active Learning"

6 / 6 papers shown
Title
Graphical Gaussian Process Regression Model for Aqueous Solvation Free
  Energy Prediction of Organic Molecules in Redox Flow Battery
Graphical Gaussian Process Regression Model for Aqueous Solvation Free Energy Prediction of Organic Molecules in Redox Flow Battery
Peiyuan Gao
Xiu Yang
Yu Tang
Muqing Zheng
Amity Anderson
V. Murugesan
Aaron Hollas
Wei Wang
37
8
0
15 Jun 2021
Nonlinear Matrix Approximation with Radial Basis Function Components
Nonlinear Matrix Approximation with Radial Basis Function Components
E. Rebrova
Yu Tang
51
0
0
03 Jun 2021
Detecting Label Noise via Leave-One-Out Cross-Validation
Detecting Label Noise via Leave-One-Out Cross-Validation
Yu-Hang Tang
Yuanran Zhu
W. A. Jong
64
3
0
21 Mar 2021
The Open Catalyst 2020 (OC20) Dataset and Community Challenges
The Open Catalyst 2020 (OC20) Dataset and Community Challenges
L. Chanussot
Abhishek Das
Siddharth Goyal
Thibaut Lavril
Muhammed Shuaibi
...
Brandon M. Wood
Junwoong Yoon
Devi Parikh
C. L. Zitnick
Zachary W. Ulissi
331
540
0
20 Oct 2020
ML4Chem: A Machine Learning Package for Chemistry and Materials Science
ML4Chem: A Machine Learning Package for Chemistry and Materials Science
Muammar El Khatib
W. A. Jong
VLM
35
6
0
02 Mar 2020
A High-Throughput Solver for Marginalized Graph Kernels on GPU
A High-Throughput Solver for Marginalized Graph Kernels on GPU
Yu-Hang Tang
Oguz Selvitopi
Doru-Thom Popovici
A. Buluç
43
7
0
14 Oct 2019
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