Publications
Rudner, T. et al. (2022) “Continual Learning via Sequential Function-Space Variational Inference”, in Proceedings of Machine Learning Research, pp. 18871–18887.
Rudner, T. et al. (2022) “Tractable Function-Space Variational Inference in Bayesian Neural Networks”, in Advances in Neural Information Processing Systems.
He, Y. et al. (2022) “MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian”, in Proceedings of Machine Learning Research.
He, Y., Reinert, G. and Cucuringu, M. (2022) “DIGRAC: Digraph Clustering Based on Flow Imbalance”, in Proceedings of Machine Learning Research.
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.
Ghalebikesabi, S. et al. (2022) “Mitigating Statistical Bias within Differentially Private Synthetic Data”, in Proceedings of Machine Learning Research, pp. 685–695.
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.
Clivio, O. et al. (2022) “Neural Score Matching for High-Dimensional Causal Inference”, in Proceedings of Machine Learning Research, pp. 7076–7110.