Yau, Christopher

17 publications

TMLR 2025 Continual Learning via Probabilistic Exchangeable Sequence Modelling Hanwen Xing, Christopher Yau

NeurIPS 2025 DoseSurv: Predicting Personalized Survival Outcomes Under Continuous-Valued Treatments Moritz Gögl, Yu Liu, Christopher Yau, Peter Watkinson, Tingting Zhu

ICLRW 2025 State-Space-like Models to Call Copy Numbers Ellen Visscher, Christopher Yau

NeurIPSW 2024 A Scalable Bayesian Continual Learning Framework for Online and Sequential Decision Making Hanwen Xing, Christopher Yau

MLHC 2024 Mixed Type Multimorbidity Variational Autoencoder: A Deep Generative Model for Multimorbidity Analysis Woojung Kim, Paul A. Jenkins, Christopher Yau

AISTATS 2022 Derivative-Based Neural Modelling of Cumulative Distribution Functions for Survival Analysis Dominic Danks, Christopher Yau

NeurIPS 2022 A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs Fabian Falck, Christopher K. I. Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C Holmes, Arnaud Doucet, Matthew Willetts

ICML 2021 BasisDeVAE: Interpretable Simultaneous Dimensionality Reduction and Feature-Level Clustering with Derivative-Based Variational Autoencoders Dominic Danks, Christopher Yau

NeurIPS 2021 Multi-Facet Clustering Variational Autoencoders Fabian Falck, Haoting Zhang, Matthew Willetts, George Nicholson, Christopher Yau, Chris C Holmes

AISTATS 2020 BasisVAE: Translation-Invariant Feature-Level Clustering with Variational Autoencoders Kaspar Märtens, Christopher Yau

AISTATS 2020 Neural Decomposition: Functional ANOVA with Variational Autoencoders Kaspar Märtens, Christopher Yau

AISTATS 2019 Augmented Ensemble MCMC Sampling in Factorial Hidden Markov Models Kaspar Märtens, Michalis Titsias, Christopher Yau

ICML 2019 Decomposing Feature-Level Variation with Covariate Gaussian Process Latent Variable Models Kaspar Märtens, Kieran Campbell, Christopher Yau

ICML 2018 Probabilistic Boolean Tensor Decomposition Tammo Rukat, Chris Holmes, Christopher Yau

ICML 2017 Bayesian Boolean Matrix Factorisation Tammo Rukat, Chris C. Holmes, Michalis K. Titsias, Christopher Yau

NeurIPS 2017 Testing and Learning on Distributions with Symmetric Noise Invariance Ho Chung Law, Christopher Yau, Dino Sejdinovic

NeurIPS 2014 Hamming Ball Auxiliary Sampling for Factorial Hidden Markov Models Michalis Titsias RC Aueb, Christopher Yau