Articles with public access mandates - Jeff SchneiderLearn more
Available somewhere: 33
Neural architecture search with bayesian optimisation and optimal transport
K Kandasamy, W Neiswanger, J Schneider, B Poczos, EP Xing
Advances in neural information processing systems 31, 2018
Mandates: US National Science Foundation, US Department of Energy, US Department of …
High dimensional Bayesian optimisation and bandits via additive models
K Kandasamy, J Schneider, B Póczos
International conference on machine learning, 295-304, 2015
Mandates: US Department of Energy
Parallelised Bayesian optimisation via Thompson sampling
K Kandasamy, A Krishnamurthy, J Schneider, B Póczos
International conference on artificial intelligence and statistics, 133-142, 2018
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Equivariance through parameter-sharing
S Ravanbakhsh, J Schneider, B Poczos
International conference on machine learning, 2892-2901, 2017
Mandates: US National Science Foundation, US Department of Energy
Multi-fidelity bayesian optimisation with continuous approximations
K Kandasamy, G Dasarathy, J Schneider, B Póczos
International conference on machine learning, 1799-1808, 2017
Mandates: US National Science Foundation, US Department of Energy
Tuning hyperparameters without grad students: Scalable and robust bayesian optimisation with dragonfly
K Kandasamy, KR Vysyaraju, W Neiswanger, B Paria, CR Collins, ...
Journal of Machine Learning Research 21 (81), 1-27, 2020
Mandates: US National Science Foundation, US Department of Energy, US Department of …
A machine learning approach for dynamical mass measurements of galaxy clusters
M Ntampaka, H Trac, DJ Sutherland, N Battaglia, B Póczos, J Schneider
The Astrophysical Journal 803 (2), 50, 2015
Mandates: US Department of Energy
Transformation autoregressive networks
J Oliva, A Dubey, M Zaheer, B Poczos, R Salakhutdinov, E Xing, ...
International Conference on Machine Learning, 3898-3907, 2018
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Beyond pinball loss: Quantile methods for calibrated uncertainty quantification
Y Chung, W Neiswanger, I Char, J Schneider
Advances in Neural Information Processing Systems 34, 10971-10984, 2021
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Multi-fidelity gaussian process bandit optimisation
K Kandasamy, G Dasarathy, J Oliva, J Schneider, B Poczos
Journal of Artificial Intelligence Research 66, 151-196, 2019
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Dynamical mass measurements of contaminated galaxy clusters using machine learning
M Ntampaka, H Trac, DJ Sutherland, S Fromenteau, B Póczos, ...
The Astrophysical Journal 831 (2), 135, 2016
Mandates: US Department of Energy
Bayesian nonparametric kernel-learning
JB Oliva, A Dubey, AG Wilson, B Póczos, J Schneider, EP Xing
Artificial intelligence and statistics, 1078-1086, 2016
Mandates: US National Science Foundation, US Department of Energy, US National …
The statistical recurrent unit
JB Oliva, B Póczos, J Schneider
International Conference on Machine Learning, 2671-2680, 2017
Mandates: US National Science Foundation, US Department of Energy
Offline contextual bayesian optimization
I Char, Y Chung, W Neiswanger, K Kandasamy, AO Nelson, M Boyer, ...
Advances in Neural Information Processing Systems 32, 2019
Mandates: US National Science Foundation
Detecting damped Ly α absorbers with Gaussian processes
R Garnett, S Ho, S Bird, J Schneider
Monthly Notices of the Royal Astronomical Society 472 (2), 1850-1865, 2017
Mandates: US National Science Foundation, US Department of Energy, US National …
Query efficient posterior estimation in scientific experiments via Bayesian active learning
K Kandasamy, J Schneider, B Póczos
Artificial Intelligence 243, 45-56, 2017
Mandates: US Department of Energy
Protein subcellular location pattern classification in cellular images using latent discriminative models
J Li, L Xiong, J Schneider, RF Murphy
Bioinformatics 28 (12), i32-i39, 2012
Mandates: US National Institutes of Health
Myopic posterior sampling for adaptive goal oriented design of experiments
K Kandasamy, W Neiswanger, R Zhang, A Krishnamurthy, J Schneider, ...
International Conference on Machine Learning, 3222-3232, 2019
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Neural dynamical systems: Balancing structure and flexibility in physical prediction
V Mehta, I Char, W Neiswanger, Y Chung, A Nelson, M Boyer, E Kolemen, ...
2021 60th IEEE Conference on Decision and Control (CDC), 3735-3742, 2021
Mandates: US National Science Foundation
DIII-D research advancing the physics basis for optimizing the tokamak approach to fusion energy
ME Fenstermacher, J Abbate, S Abe, T Abrams, M Adams, B Adamson, ...
Nuclear Fusion 62 (4), 042024, 2022
Mandates: US Department of Energy
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