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stat.ML2026
Metropolis-Adjusted Diffusion Models
Kevin H. Lam, Tyler Farghly, Christopher Williams +3
Sampling from score-based diffusion models incurs bias due to both time discretisation and the approximation of the score function. A common strategy for reducing this bias is to a…
stat.ML2025
CN-SBM: Categorical Block Modelling For Primary and Residual Copy Number Variation
Kevin Lam, William Daniels, J Maxwell Douglas +4
Cancer is a genetic disorder whose clonal evolution can be monitored by tracking noisy genome-wide copy number variants. We introduce the Copy Number Stochastic Block Model (CN-SBM…
stat.ML2025
Rao-Blackwellised Reparameterisation Gradients
Kevin H. Lam, Thang D. Bui, George Deligiannidis +1
Latent Gaussian variables have been popularised in probabilistic machine learning. In turn, gradient estimators are the machinery that facilitates gradient-based optimisation for m…