Victor Veitch
Victor Veitch
Google, University of Chicago
Verified email at - Homepage
Cited by
Cited by
Contextuality supplies the ‘magic’for quantum computation
M Howard, J Wallman, V Veitch, J Emerson
Nature 510 (7505), 351-355, 2014
Negative quasi-probability as a resource for quantum computation
V Veitch, C Ferrie, D Gross, J Emerson
New Journal of Physics 14 (11), 113011, 2012
The resource theory of stabilizer quantum computation
V Veitch, SAH Mousavian, D Gottesman, J Emerson
New Journal of Physics 16 (1), 013009, 2014
Efficient simulation scheme for a class of quantum optics experiments with non-negative Wigner representation
V Veitch, N Wiebe, C Ferrie, J Emerson
New Journal of Physics 15 (1), 013037, 2013
The class of random graphs arising from exchangeable random measures
V Veitch, DM Roy
arXiv preprint arXiv:1512.03099, 2015
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
Adapting neural networks for the estimation of treatment effects
C Shi, DM Blei, V Veitch
arXiv preprint arXiv:1906.02120, 2019
Sampling and estimation for (sparse) exchangeable graphs
V Veitch, DM Roy
Annals of Statistics 47 (6), 3274-3299, 2019
Sampling perspectives on sparse exchangeable graphs
C Borgs, JT Chayes, H Cohn, V Veitch
Annals of Probability 47 (5), 2754-2800, 2019
The holdout randomization test: Principled and easy black box feature selection
W Tansey, V Veitch, H Zhang, R Rabadan, DM Blei
arXiv preprint arXiv:1811.00645, 2018
The whole is greater than the sum of the parts: on the possibility of purely statistical interpretations of quantum theory
J Emerson, D Serbin, C Sutherland, V Veitch
arXiv preprint arXiv:1312.1345, 2013
Underspecification presents challenges for credibility in modern machine learning
A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ...
arXiv preprint arXiv:2011.03395, 2020
Adapting text embeddings for causal inference
V Veitch, D Sridhar, D Blei
Conference on Uncertainty in Artificial Intelligence, 919-928, 2020
Using embeddings to correct for unobserved confounding in networks
V Veitch, Y Wang, DM Blei
arXiv preprint arXiv:1902.04114, 2019
Corrigendum: Negative quasi-probability as a resource for quantum computation
V Veitch, C Ferrie, D Gross, J Emerson
New Journal of Physics 15 (3), 039502, 2013
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
An estimator for the tail-index of graphex processes
Z Naulet, E Sharma, V Veitch, DM Roy
arXiv preprint arXiv:1712.01745, 2017
Negative Quasi-Probability in the Context of Quantum Computation
V Veitch
University of Waterloo, 2013
Negative quasi-probability, contextuality, quantum magic and the power of quantum computation
J Emerson, D Gottesman, A Hamed, C Ferrie, D Gross
Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding
V Veitch, A Zaveri
arXiv preprint arXiv:2003.01747, 2020
The system can't perform the operation now. Try again later.
Articles 1–20