| Scalable log determinants for Gaussian process kernel learning K Dong, D Eriksson, H Nickisch, D Bindel, AG Wilson Advances in Neural Information Processing Systems, 2017 | 114 | 2017 |
| Scaling Gaussian process regression with derivatives D Eriksson, K Dong, EH Lee, D Bindel, AG Wilson Advances in Neural Information Processing Systems, 2018 | 106 | 2018 |
| Network density of states K Dong, AR Benson, D Bindel Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 55 | 2019 |
| Interpolative separable density fitting through centroidal voronoi tessellation with applications to hybrid functional electronic structure calculations K Dong, W Hu, L Lin Journal of Chemical Theory and Computation 14 (3), 1311-1320, 2018 | 55 | 2018 |
| Advising caution in studying seasonal oscillations in crime rates K Dong, Y Cao, B Siercke, M Wilber, SG McCalla PLoS one 12 (9), e0185432, 2017 | 8 | 2017 |
| Advances in Neural Information Processing Systems 31 D Eriksson, K Dong, E Lee, D Bindel, AG Wilson Curran Associates, Inc., 2018 | 4 | 2018 |
| Modified kernel polynomial method for estimating graph spectra D Bindel, K Dong Proceedings of the SIAM Workshop on Network Science, Snowbird, UT, USA, 15-16, 2015 | 1 | 2015 |
| On-the-Fly Rectification for Robust Large-Vocabulary Topic Inference M Lee, S Cho, K Dong, D Mimno, D Bindel International Conference on Machine Learning, 6087-6097, 2021 | | 2021 |
| Stochastic Estimators in Gaussian Process Kernel Learning D Bindel, K Dong, D Eriksson, A Wilson HOUSEHOLDER SYMPOSIUM XX PROGRAM AND ABSTRACTS, 32, 0 | | |
