Research
StatML Publications
Here is a selection of published outputs from our StatML students.
Simultaneous global and local clustering in multiplex networks with covariate information
Published in: Journal of Complex Networks
Accelerated parallel tempering via neural transports
Published in: The Fourteenth International Conference on Learning Representations (ICLR 2026)
CREPE: controlling diffusion with replica exchange
Published in: The Fourteenth International Conference on Learning Representations (ICLR 2026)
SigmaDock: untwisting molecular docking with fragment-based SE(3) diffusion
Published in: The Fourteenth International Conference on Learning Representations (ICLR 2026)
Online spectral density estimation
Published in: Journal of Computational and Graphical Statistics
A novel framework for quantifying nominal outlyingness
Published in: Statistics and Computing
Factor-driven network informed restricted vector autoregression
Published in: Proceedings of the 6th ACM International Conference on AI in Finance (ICAIF 2025)
Learning Latent Variable Models via Jarzynski-adjusted Langevin Algorithm
Published in: The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025)
Adjusting model size in continual Gaussian processes: how big is big enough?
Published in: Forty-second International Conference on Machine Learning (ICML 2025)
Step-DAD: Semi-amortized policy-based Bayesian experimental design
Published in: Forty-second International Conference on Machine Learning (ICML 2025)
Dual feature reduction for the sparse-group lasso and its adaptive variant
Published in: Forty-second International Conference on Machine Learning (ICML 2025)
Online Bayesian changepoint detection for network Poisson processes with community structure
Published in: Statistics and Computing