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Publications

Clivio, O. et al. (2022) “Neural Score Matching for High-Dimensional Causal Inference”, in Proceedings of Machine Learning Research, pp. 7076–7110.
Rudner, T. et al. (2022) “Tractable Function-Space Variational Inference in Bayesian Neural Networks”, in Advances in Neural Information Processing Systems.
Rudner, T. et al. (2022) “Continual Learning via Sequential Function-Space Variational Inference”, in Proceedings of Machine Learning Research, pp. 18871–18887.
Miao, N. et al. (2022) “ON INCORPORATING INDUCTIVE BIASES INTO VAES”, in Iclr 2022 10th International Conference on Learning Representations.
Xu, W. and Reinert, G. (2022) “A Kernelised Stein Statistic for Assessing Implicit Generative Models”, in Advances in Neural Information Processing Systems.
Xu, W. and Reinert, G. (2022) “AgraSSt: Approximate Graph Stein Statistics for Interpretable Assessment of Implicit Graph Generators”, in Advances in Neural Information Processing Systems.
Cornish, R. et al. (2022) “Conformal Off-Policy Prediction in Contextual Bandits”, in. Curran Associates, pp. 31512–31524.
He, Y. et al. (2022) “MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian”, in Proceedings of Machine Learning Research.
Ghalebikesabi, S. et al. (2022) “Mitigating Statistical Bias within Differentially Private Synthetic Data”, in Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence, UAI 2022, pp. 696–705.
Ghalebikesabi, S. et al. (2022) “Mitigating Statistical Bias within Differentially Private Synthetic Data”, in Proceedings of Machine Learning Research, pp. 685–695.