This year members of the Institute for Statistical Science within the School of Mathematics and their collaborators from across the University and other institutions have three papers accepted at the NeurIPS conference, to be held in Vancouver Canada.

"Conditional Outcome Equivalence: A Quantile Alternative to CATE"
by Josh Givens, Henry Reeve, Song Liu, Katarzyna Reluga

"Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows"
by Alberto Cabezas, Louis Sharrock, Christopher Nemeth

"Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines"
by Edward Milsom, Ben Anson, Laurence Aitchison

NeurIPS is one of the most prestigious conferences and publication venues in Machine Learning, Artificial Intelligence and related areas. Over 12000 papers were submitted to NeurIPS last year, with an acceptance rate of approximately 26%.