| Contextuality supplies the ‘magic’for quantum computation M Howard, J Wallman, V Veitch, J Emerson Nature 510 (7505), 351-355, 2014 | 562 | 2014 |
| Underspecification presents challenges for credibility in modern machine learning A D’Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ... Journal of Machine Learning Research, 2020 | 395 | 2020 |
| The resource theory of stabilizer quantum computation V Veitch, SAH Mousavian, D Gottesman, J Emerson New Journal of Physics 16 (1), 013009, 2014 | 305 | 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 | 300 | 2012 |
| Adapting neural networks for the estimation of treatment effects C Shi, D Blei, V Veitch Advances in neural information processing systems 32, 2019 | 178 | 2019 |
| 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 | 152* | 2018 |
| 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 | 111 | 2013 |
| The class of random graphs arising from exchangeable random measures V Veitch, DM Roy arXiv preprint arXiv:1512.03099, 2015 | 106 | 2015 |
| Adapting text embeddings for causal inference V Veitch, D Sridhar, D Blei Conference on Uncertainty in Artificial Intelligence, 919-928, 2020 | 71 | 2020 |
| Causal inference in natural language processing: Estimation, prediction, interpretation and beyond A Feder, KA Keith, E Manzoor, R Pryzant, D Sridhar, Z Wood-Doughty, ... Transactions of the Association for Computational Linguistics 10, 1138-1158, 2022 | 62 | 2022 |
| Counterfactual invariance to spurious correlations in text classification V Veitch, A D'Amour, S Yadlowsky, J Eisenstein Advances in neural information processing systems 34, 16196-16208, 2021 | 62* | 2021 |
| 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 1 (3), 2018 | 53* | 2018 |
| Using embeddings to correct for unobserved confounding in networks V Veitch, Y Wang, D Blei Advances in Neural Information Processing Systems 32, 2019 | 48* | 2019 |
| Sampling and estimation for (sparse) exchangeable graphs V Veitch, DM Roy | 42 | 2019 |
| Sampling perspectives on sparse exchangeable graphs C Borgs, JT Chayes, H Cohn, V Veitch | 27 | 2019 |
| Sense and sensitivity analysis: Simple post-hoc analysis of bias due to unobserved confounding V Veitch, A Zaveri Advances in Neural Information Processing Systems 33, 10999-11009, 2020 | 25 | 2020 |
| Causal effects of linguistic properties R Pryzant, D Card, D Jurafsky, V Veitch, D Sridhar arXiv preprint arXiv:2010.12919, 2020 | 24 | 2020 |
| 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 | 24 | 2013 |
| Invariant representation learning for treatment effect estimation C Shi, V Veitch, DM Blei Uncertainty in Artificial Intelligence, 1546-1555, 2021 | 13 | 2021 |
| Valid causal inference with (some) invalid instruments JS Hartford, V Veitch, D Sridhar, K Leyton-Brown International Conference on Machine Learning, 4096-4106, 2021 | 12 | 2021 |
Joseph EmersonProfessor of Applied Math, University of WaterlooVerified email at uwaterloo.ca
