Michael Mccourt
Michael Mccourt
Research & Development, Distributional
Verified email at - Homepage
Cited by
Cited by
Multiphysics simulations: Challenges and opportunities
DE Keyes, LC McInnes, C Woodward, W Gropp, E Myra, M Pernice, J Bell, ...
The International Journal of High Performance Computing Applications 27 (1 …, 2013
Kernel-based approximation methods using Matlab
GE Fasshauer, MJ McCourt
World Scientific Publishing Company, 2015
Stable evaluation of Gaussian radial basis function interpolants
GE Fasshauer, MJ McCourt
SIAM Journal on Scientific Computing 34 (2), A737-A762, 2012
Bayesian optimization is superior to random search for machine learning hyperparameter tuning: Analysis of the black-box optimization challenge 2020
R Turner, D Eriksson, M McCourt, J Kiili, E Laaksonen, Z Xu, I Guyon
Proceedings of the NeurIPS 2020 Competition and Demonstration Track 133, 3-26, 2021
Bayesian optimization for machine learning: A practical guidebook
I Dewancker, M McCourt, S Clark
arXiv preprint arXiv:1612.04858, 2016
Bayesian optimization primer
I Dewancker, M McCourt, S Clark
URL https://app. sigopt. com/static/pdf/SigOpt_ Bayesian_Optimization_Primer …, 2015
Practical Bayesian optimization in the presence of outliers
R Martinez-Cantin, K Tee, M McCourt
International conference on artificial intelligence and statistics, 1722-1731, 2018
An introduction to the Hilbert-Schmidt SVD using iterated Brownian bridge kernels
R Cavoretto, GE Fasshauer, M McCourt
Numerical Algorithms 68, 393-422, 2015
A stratified analysis of Bayesian optimization methods
I Dewancker, M McCourt, S Clark, P Hayes, A Johnson, G Ke
arXiv preprint arXiv:1603.09441, 2016
Creating glasswing butterfly-inspired durable antifogging superomniphobic supertransmissive, superclear nanostructured glass through Bayesian learning and optimization
S Haghanifar, M McCourt, B Cheng, J Wuenschell, P Ohodnicki, PW Leu
Materials Horizons 6 (8), 1632-1642, 2019
The method of fundamental solutions in solving coupled boundary value problems for M/EEG
G Ala, GE Fasshauer, E Francomano, S Ganci, MJ McCourt
SIAM Journal on Scientific Computing 37 (4), B570-B590, 2015
A strategy for ranking optimization methods using multiple criteria
I Dewancker, M McCourt, S Clark, P Hayes, A Johnson, G Ke
Workshop on Automatic Machine Learning, 11-20, 2016
Systems and methods implementing an intelligent optimization platform
P Hayes, M McCourt, A Johnson, G Ke, S Clark
US Patent 10,217,061, 2019
A meshfree solver for the MEG forward problem
G Ala, E Francomano, GE Fasshauer, S Ganci, MJ McCourt
IEEE Transactions on Magnetics 51 (3), 1-4, 2015
An augmented MFS approach for brain activity reconstruction
G Ala, GE Fasshauer, E Francomano, S Ganci, MJ McCourt
Mathematics and Computers in Simulation 141, 3-15, 2017
Discovering high-performance broadband and broad angle antireflection surfaces by machine learning
S Haghanifar, M McCourt, B Cheng, J Wuenschell, P Ohodnicki, PW Leu
Optica 7 (7), 784-789, 2020
Beyond the pareto efficient frontier: Constraint active search for multiobjective experimental design
G Malkomes, B Cheng, EH Lee, M Mccourt
International Conference on Machine Learning, 7423-7434, 2021
Sparse matrix-matrix products executed through coloring
M McCourt, B Smith, H Zhang
SIAM Journal on Matrix Analysis and Applications 36 (1), 90-109, 2015
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
Bayesian optimization with approximate set kernels
J Kim, M McCourt, T You, S Kim, S Choi
Machine Learning 110, 857-879, 2021
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