Wenda Zhou
Wenda Zhou
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Cited by
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Non-vacuous generalization bounds at the imagenet scale: a PAC-bayesian compression approach
W Zhou, V Veitch, M Austern, RP Adams, P Orbanz
arXiv preprint arXiv:1804.05862, 2018
Sketchgraphs: A large-scale dataset for modeling relational geometry in computer-aided design
A Seff, Y Ovadia, W Zhou, RP Adams
arXiv preprint arXiv:2007.08506, 2020
Autobahn: Automorphism-based graph neural nets
E Thiede, W Zhou, R Kondor
Advances in Neural Information Processing Systems 34, 29922-29934, 2021
Vitruvion: A generative model of parametric cad sketches
A Seff, W Zhou, N Richardson, RP Adams
arXiv preprint arXiv:2109.14124, 2021
Asymptotics of cross-validation
M Austern, W Zhou
arXiv preprint arXiv:2001.11111, 2020
Discrete object generation with reversible inductive construction
A Seff, W Zhou, F Damani, A Doyle, RP Adams
Advances in neural information processing systems 32, 2019
Approximate leave-one-out for fast parameter tuning in high dimensions
S Wang, W Zhou, H Lu, A Maleki, V Mirrokni
International Conference on Machine Learning, 5228-5237, 2018
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions
KR Rad, W Zhou, A Maleki
International Conference on Artificial Intelligence and Statistics, 4067-4077, 2020
Approximate leave-one-out for high-dimensional non-differentiable learning problems
S Wang, W Zhou, A Maleki, H Lu, V Mirrokni
arXiv preprint arXiv:1810.02716, 2018
Empirical risk minimization and stochastic gradient descent for relational data
V Veitch, M Austern, W Zhou, DM Blei, P Orbanz
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
Analysis of genotype by methylation interactions through sparsity-inducing regularized regression
W Zhou, SH Lo
BMC proceedings 12 (Suppl 9), 40, 2018
Compressed sensing in the presence of speckle noise
W Zhou, S Jalali, A Maleki
IEEE Transactions on Information Theory 68 (10), 6964-6980, 2022
Towards theoretically-founded learning-based denoising
W Zhou, S Jalali
2019 IEEE International Symposium on Information Theory (ISIT), 2714-2718, 2019
Graph neural networks for biochemistry that incorporate substructure
EH Thiede, W Zhou, R Kondor
Biophysical Journal 121 (3), 531a, 2022
The challenge of detecting genotype-by-methylation interaction: GAW20
M De Andrade, E Warwick Daw, AT Kraja, V Fisher, L Wang, K Hu, J Li, ...
BMC genetics 19, 119-125, 2018
Denoising of structured random processes
W Zhou, S Jalali
arXiv preprint arXiv:1901.05937, 2019
Correction to” Compressed sensing in the presence of speckle noise”
W Zhou, S Jalali, A Maleki
IEEE Transactions on Information Theory, 2024
Bayesian denoising of structured sources and its implications on learning-based denoising
W Zhou, J Wabnig, S Jalali
Information and Inference: A Journal of the IMA 12 (4), 2503-2545, 2023
Graph Neural Networks that incorporate Physical Structure
E Thiede, W Zhou, R Kondor
APS March Meeting Abstracts 2022, S01. 002, 2022
New Perspectives in Cross-Validation
W Zhou
Columbia University, 2020
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