| 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 23 (226), 1-61, 2022 | 1030 | 2022 |
| Contextuality supplies the ‘magic’for quantum computation M Howard, J Wallman, V Veitch, J Emerson Nature 510 (7505), 351-355, 2014 | 843 | 2014 |
| The resource theory of stabilizer quantum computation V Veitch, SAH Mousavian, D Gottesman, J Emerson New Journal of Physics 16 (1), 013009, 2014 | 668 | 2014 |
| Adapting neural networks for the estimation of treatment effects C Shi, D Blei, V Veitch Advances in neural information processing systems 32, 2019 | 609 | 2019 |
| 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 | 495 | 2012 |
| The linear representation hypothesis and the geometry of large language models K Park, YJ Choe, V Veitch arXiv preprint arXiv:2311.03658, 2023 | 403 | 2023 |
| 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 | 372 | 2022 |
| 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 | 273 | 2018 |
| Counterfactual invariance to spurious correlations: Why and how to pass stress tests V Veitch, A D'Amour, S Yadlowsky, J Eisenstein arXiv preprint arXiv:2106.00545, 2021 | 208* | 2021 |
| Adapting text embeddings for causal inference V Veitch, D Sridhar, D Blei Conference on uncertainty in artificial intelligence, 919-928, 2020 | 204 | 2020 |
| 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 | 154 | 2013 |
| The class of random graphs arising from exchangeable random measures V Veitch, DM Roy arXiv preprint arXiv:1512.03099, 2015 | 120 | 2015 |
| Concept algebra for (score-based) text-controlled generative models Z Wang, L Gui, J Negrea, V Veitch Advances in Neural Information Processing Systems 36, 35331-35349, 2023 | 104* | 2023 |
| Using embeddings to correct for unobserved confounding in networks V Veitch, Y Wang, D Blei Advances in Neural Information Processing Systems 32, 2019 | 100 | 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 1 (3), 2018 | 100* | 2018 |
| The geometry of categorical and hierarchical concepts in large language models K Park, YJ Choe, Y Jiang, V Veitch arXiv preprint arXiv:2406.01506, 2024 | 93 | 2024 |
| Bonbon alignment for large language models and the sweetness of best-of-n sampling L Gui, C Gârbacea, V Veitch Advances in Neural Information Processing Systems 37, 2851-2885, 2024 | 86 | 2024 |
| 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 | 72 | 2020 |
| Causal effects of linguistic properties R Pryzant, D Card, D Jurafsky, V Veitch, D Sridhar Proceedings of the 2021 Conference of the North American Chapter of the …, 2021 | 66 | 2021 |
| Sampling and estimation for (sparse) exchangeable graphs V Veitch, DM Roy | 60 | 2019 |
Joseph EmersonProfessor of Applied Math, University of WaterlooVerified email at uwaterloo.ca
