Mike Wu
Title
Cited by
Cited by
Year
Beyond sparsity: Tree regularization of deep models for interpretability
M Wu, M Hughes, S Parbhoo, M Zazzi, V Roth, F Doshi-Velez
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
1332018
Multimodal generative models for scalable weakly-supervised learning
M Wu, N Goodman
arXiv preprint arXiv:1802.05335, 2018
992018
Understanding vasopressor intervention and weaning: risk prediction in a public heterogeneous clinical time series database
M Wu, M Ghassemi, M Feng, LA Celi, P Szolovits, F Doshi-Velez
Journal of the American Medical Informatics Association 24 (3), 488-495, 2017
462017
Predicting intervention onset in the ICU with switching state space models
M Ghassemi, M Wu, MC Hughes, P Szolovits, F Doshi-Velez
AMIA Summits on Translational Science Proceedings 2017, 82, 2017
392017
Zero shot learning for code education: Rubric sampling with deep learning inference
M Wu, M Mosse, N Goodman, C Piech
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 782-790, 2019
192019
On mutual information in contrastive learning for visual representations
M Wu, C Zhuang, M Mosse, D Yamins, N Goodman
arXiv preprint arXiv:2005.13149, 2020
112020
Meta-amortized variational inference and learning
K Choi, M Wu, N Goodman, S Ermon
arXiv preprint arXiv:1902.01950, 2019
11*2019
Differentiable antithetic sampling for variance reduction in stochastic variational inference
M Wu, N Goodman, S Ermon
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
102019
Pragmatic inference and visual abstraction enable contextual flexibility during visual communication
JE Fan, RD Hawkins, M Wu, ND Goodman
Computational Brain & Behavior 3 (1), 86-101, 2020
82020
Variational item response theory: Fast, accurate, and expressive
M Wu, RL Davis, BW Domingue, C Piech, N Goodman
arXiv preprint arXiv:2002.00276, 2020
52020
Regional tree regularization for interpretability in black box models
M Wu, S Parbhoo, M Hughes, R Kindle, L Celi, M Zazzi, V Roth, ...
arXiv preprint arXiv:1908.04494, 2019
52019
Viewmaker Networks: Learning Views for Unsupervised Representation Learning
A Tamkin, M Wu, N Goodman
arXiv preprint arXiv:2010.07432, 2020
42020
Generative Grading: Near Human-level Accuracy for Automated Feedback on Richly Structured Problems
A Malik, M Wu, V Vasavada, J Song, M Coots, J Mitchell, N Goodman, ...
arXiv preprint arXiv:1905.09916, 2019
42019
Computing engine, software, system and method
F Wood, M Wu, Y Perov, H Yang
US Patent App. 15/465,131, 2017
42017
Financial market prediction
M Wu
arXiv preprint arXiv:1503.02328, 2015
32015
Regional tree regularization for interpretability in deep neural networks
M Wu, S Parbhoo, M Hughes, R Kindle, L Celi, M Zazzi, V Roth, ...
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 6413-6421, 2020
22020
Optimizing for interpretability in deep neural networks with tree regularization
M Wu, S Parbhoo, MC Hughes, V Roth, F Doshi-Velez
arXiv preprint arXiv:1908.05254, 2019
22019
Beyond sparsity: Tree-based regularization of deep models for interpretability
M Wu, M Hughes, S Parbhoo, F Doshi-Velez
In: Neural Information Processing Systems (NIPS) Conference. Transparent and …, 2017
22017
Spreadsheet probabilistic programming
M Wu, Y Perov, F Wood, H Yang
arXiv preprint arXiv:1606.04216, 2016
22016
HarperValleyBank: A Domain-Specific Spoken Dialog Corpus
M Wu, J Nafziger, A Scodary, A Maas
arXiv preprint arXiv:2010.13929, 2020
12020
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