Publications

Reichelt, T. et al. (2022) “Expectation Programming: Adapting Probabilistic Programming Systems to Estimate Expectations Efficiently”, in Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence, UAI 2022, pp. 1676–1685.

Rudner, T. et al. (2022) “Tractable Function-Space Variational Inference in Bayesian Neural Networks”, 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.

Rudner, T. et al. (2022) “Continual Learning via Sequential Function-Space Variational Inference”, in Proceedings of Machine Learning Research, pp. 18871–18887.

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 the 38th Conference on Uncertainty in Artificial Intelligence, UAI 2022, pp. 696–705.

He, Y. et al. (2022) “MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed Laplacian”, 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.

Venkatesh, S. et al. (2022) “Genetic architecture of longitudinal obesity trajectories in primary care electronic health records”, in HUMAN HEREDITY, pp. 21–22.

Clivio, O. et al. (2022) “Neural Score Matching for High-Dimensional Causal Inference”, in Proceedings of Machine Learning Research, pp. 7076–7110.