Publications

Tirumala, D. et al. (2022) “Behavior Priors for Efficient Reinforcement Learning”, Journal of Machine Learning Research, 23.

Nicholson, G. et al. (2022) “Multivariate phenotype analysis enables genome-wide inference of mammalian gene function”, PLOS Biology, 20(8), p. e3001723.

Jersakova, R. et al. (2022) “Bayesian Imputation of COVID-19 Positive Test Counts for Nowcasting Under Reporting Lag”, Journal of the Royal Statistical Society Series C (Applied Statistics), 71(4), pp. 834–860.

Pardo-Diaz, J. et al. (2022) “Generating weighted and thresholded gene coexpression networks using signed distance correlation.”, Network Science, 10(2), pp. 131–145.

Benedetto, U. et al. (2022) “Machine learning improves mortality risk prediction after cardiac surgery: Systematic review and meta-analysis”, Journal of Thoracic and Cardiovascular Surgery, 163(Int Stat Rev 80 2012), pp. 2075 – 2087.e9.

Campbell, A. et al. (2022) “Online variational filtering and parameter learning”, in Advances in Neural Information Processing Systems 34 (NeurIPS 2021). Curran Associates, pp. 18633–18645.

Pardo-Diaz, J. et al. (2022) “Extracting information from gene coexpression networks of Rhizobium leguminosarum”, Journal of Computational Biology, 29(7), pp. 752–768.

Lee, H. et al. (2022) “Deep neural networks with dependent weights: Gaussian Process mixture limit, heavy tails, sparsity and compressibility”, arXiv.