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Agrawal, N., Shamsabadi, A. S., Kusner, M. J., & Gascón, A. (novembre 2019). QUOTIENT: two-party secure neural network training and prediction [Communication écrite]. ACM SIGSAC Conference on Computer and Communications Security (CCS 2019), London, United Kingdom. Lien externe
Bradshaw, J., Kusner, M. J., Paige, B., Segler, M. H. S., & Hernández-Lobato, J. M. (mai 2019). A generative model for electron paths [Communication écrite]. 7th International Conference on Learning Representations (ICLR 2019), New Orleans, Louisiana, USA (19 pages). Lien externe
Bradshaw, J., Paige, B., Kusner, M. J., Segler, M. H. S., & Hernández-Lobato, J. M. (décembre 2019). A model to search for synthesizable molecules [Communication écrite]. 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada. Lien externe
Kilbertus, N., Ball, P. J., Kusner, M. J., Weller, A., & Silva, R. (juillet 2019). The Sensitivity of Counterfactual Fairness to Unmeasured Confounding [Communication écrite]. 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019), Tel Aviv, Israel. Publié dans Proceedings of Machine Learning Research, 115. Lien externe
Kusner, M. J., Russell, C., Loftus, J. R., & Silva, R. (juin 2019). Making Decisions that Reduce Discriminatory Impact [Communication écrite]. 36th International Conference on Machine Learning (ICML 2019), Long Beach, California, USA. Publié dans Proceedings of Machine Learning Research, 97. Lien externe
