David Eriksson
David Eriksson
Research Scientist at Facebook Research
Verified email at fb.com - Homepage
Title
Cited by
Cited by
Year
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
622017
Scalable Global Optimization via Local Bayesian Optimization
D Eriksson, M Pearce, J Gardner, RD Turner, M Poloczek
Advances in Neural Information Processing Systems, 2019
452019
Scaling Gaussian Process Regression with Derivatives
D Eriksson, K Dong, EH Lee, D Bindel, AG Wilson
Advances in Neural Information Processing Systems, 2018
322018
Continental hydrology loading observed by VLBI measurements
D Eriksson, DS MacMillan
Journal of Geodesy 88 (7), 675-690, 2014
272014
Tropospheric delay ray tracing applied in VLBI analysis
D Eriksson, DS MacMillan, JM Gipson
Journal of Geophysical Research: Solid Earth 119 (12), 9156-9170, 2014
202014
Surrogate optimization toolbox (pySOT)
D Eriksson, D Bindel, C Shoemaker
github.com/dme65/pySOT, 2015
122015
pySOT and POAP: An Event-Driven Asynchronous Framework for Surrogate Optimization
D Eriksson, D Bindel, CA Shoemaker
arXiv preprint arXiv:1908.00420, 2019
102019
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization
G Pleiss, M Jankowiak, D Eriksson, A Damle, JR Gardner
Advances in Neural Information Processing Systems, 2020
42020
Scalable constrained bayesian optimization
D Eriksson, M Poloczek
International Conference on Artificial Intelligence and Statistics, 730-738, 2021
32021
Approximate distance queries for path-planning in massive point clouds
D Eriksson, E Shellshear
2014 11th International Conference on Informatics in Control, Automation and …, 2014
32014
Efficient Rollout Strategies for Bayesian Optimization
E Lee, D Eriksson, D Bindel, B Cheng, M Mccourt
Conference on Uncertainty in Artificial Intelligence, 260-269, 2020
12020
Point cloud simplification and processing for path-planning
D Eriksson
12014
Tropospheric Delay Raytracing Applied in VLBI Analysis
DS MacMillan, D Eriksson, JM Gipson
AGU Fall Meeting Abstracts 2013, G43A-0965, 2013
12013
Resource optimization with simultaneous trust region modeling
DM Eriksson, MAL Pearce, J Gardner, RD Turner, MU Poloczek
US Patent App. 17/010,725, 2021
2021
Constraint resource optimization using trust region modeling
DM Eriksson, MU Poloczek
US Patent App. 17/076,103, 2021
2021
High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces
D Eriksson, M Jankowiak
arXiv preprint arXiv:2103.00349, 2021
2021
Scalable kernel methods and their use in black-box optimization
D Eriksson
2018
Fast exact shortest distance queries for massive point clouds
D Eriksson, E Shellshear
Graphical Models 84, 28-37, 2016
2016
Supplementary Material: Scalable Constrained Bayesian Optimization
D Eriksson, M Poloczek
Stochastic Estimators in Gaussian Process Kernel Learning
D Bindel, K Dong, D Eriksson, A Wilson
HOUSEHOLDER SYMPOSIUM XX PROGRAM AND ABSTRACTS, 32, 0
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