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Willie Neiswanger
Willie Neiswanger
Postdoc, Computer Science, Stanford University
Verified email at cs.stanford.edu - Homepage
Title
Cited by
Cited by
Year
Neural architecture search with bayesian optimisation and optimal transport
K Kandasamy, W Neiswanger, J Schneider, B Poczos, E Xing
Proceedings of the 32nd International Conference on Neural Information …, 2018
5082018
Asymptotically Exact, Embarrassingly Parallel MCMC
W Neiswanger, C Wang, E Xing
3772014
Bananas: Bayesian optimization with neural architectures for neural architecture search
C White, W Neiswanger, Y Savani
Proceedings of the AAAI Conference on Artificial Intelligence 35, 2021
1722021
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
1362020
Methods for comparing uncertainty quantifications for material property predictions
K Tran, W Neiswanger, J Yoon, Q Zhang, E Xing, ZW Ulissi
Machine Learning: Science and Technology 1 (2), 025006, 2020
952020
Chembo: Bayesian optimization of small organic molecules with synthesizable recommendations
K Korovina, S Xu, K Kandasamy, W Neiswanger, B Poczos, J Schneider, ...
International Conference on Artificial Intelligence and Statistics, 3393-3403, 2020
822020
A study on encodings for neural architecture search
C White, W Neiswanger, S Nolen, Y Savani
Advances in Neural Information Processing Systems 33, 2020
562020
Pollux: Co-adaptive Cluster Scheduling for Goodput-Optimized Deep Learning.
A Qiao, SK Choe, SJ Subramanya, W Neiswanger, Q Ho, H Zhang, ...
OSDI 21, 1-18, 2021
532021
Interactive Weak Supervision: Learning Useful Heuristics for Data Labeling
B Boecking, W Neiswanger, E Xing, A Dubrawski
International Conference on Learning Representations (ICLR), 2021
492021
Parallel and distributed block-coordinate frank-wolfe algorithms
YX Wang, V Sadhanala, W Dai, W Neiswanger, S Sra, E Xing
International Conference on Machine Learning, 1548-1557, 2016
442016
Fast distribution to real regression
J Oliva, W Neiswanger, B Póczos, J Schneider, E Xing
Artificial Intelligence and Statistics, 706-714, 2014
432014
The dependent Dirichlet process mixture of objects for detection-free tracking and object modeling
W Neiswanger, F Wood, E P Xing
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2014
42*2014
Durable interactions of T cells with T cell receptor stimuli in the absence of a stable immunological synapse
V Mayya, E Judokusumo, EA Shah, CG Peel, W Neiswanger, D Depoil, ...
Cell reports 22 (2), 340-349, 2018
412018
Beyond pinball loss: Quantile methods for calibrated uncertainty quantification
Y Chung, W Neiswanger, I Char, J Schneider
Proceedings of the 35th International Conference on Neural Information …, 2021
322021
Uncertainty toolbox: an open-source library for assessing, visualizing, and improving uncertainty quantification
Y Chung, I Char, H Guo, J Schneider, W Neiswanger
arXiv preprint arXiv:2109.10254, 2021
302021
Fast function to function regression
J Oliva, W Neiswanger, B Póczos, E Xing, H Trac, S Ho, J Schneider
Artificial Intelligence and Statistics, 717-725, 2015
292015
Offline contextual bayesian optimization
I Char, Y Chung, W Neiswanger, K Kandasamy, AO Nelson, M Boyer, ...
Advances in Neural Information Processing Systems 32, 2019
28*2019
Generalized Pólya urn for time-varying Pitman-Yor processes
F Caron, W Neiswanger, F Wood, A Doucet, M Davy
Journal of Machine Learning Research 18 (27), 2017
242017
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
22*2019
Post-inference Methods for Scalable Probabilistic Modeling and Sequential Decision Making
W Neiswanger
Carnegie Mellon University, 2019
22*2019
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Articles 1–20