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PHAISTOS: A framework for Markov chain Monte Carlo simulation and inference of protein structure., , , , , , , , , and 7 other author(s). Journal of Computational Chemistry, 34 (19): 1697-1705 (2013)Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation., , and . ECML/PKDD (1), volume 10534 of Lecture Notes in Computer Science, page 513-529. Springer, (2017)Bayesian Generalised Ensemble Markov Chain Monte Carlo., , , and . AISTATS, volume 51 of JMLR Workshop and Conference Proceedings, page 408-416. JMLR.org, (2016)A Probabilistic Model of RNA Conformational Space., , , , , and . PLoS Computational Biology, (2009)missIWAE: Deep Generative Modelling and Imputation of Incomplete Data., and . CoRR, (2018)MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets., and . ICML, volume 97 of Proceedings of Machine Learning Research, page 4413-4423. PMLR, (2019)Beyond rotamers: a generative, probabilistic model of side chains in proteins., , , , , and . BMC Bioinformatics, (2010)Fast Bayesian Non-Negative Matrix Factorisation and Tri-Factorisation., , and . CoRR, (2016)Leveraging the Exact Likelihood of Deep Latent Variable Models., and . NeurIPS, page 3859-3870. (2018)Uphill Roads to Variational Tightness: Monotonicity and Monte Carlo Objectives., and . CoRR, (2022)