Ensemble Distribution Distillation. - Andrey Malinin; Bruno Mlodozeniec; Mark J. F. Gales (ICLR, 2020)

Hyperparameter Optimization through Neural Network Partitioning. - Bruno Mlodozeniec; Matthias Reisser; Christos Louizos (ICLR, 2023)

Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics. - Leon Klein; Andrew Y. K. Foong; Tor Erlend Fjelde; Bruno Mlodozeniec; Marc Brockschmidt; Sebastian Nowozin; Frank Noé; Ryota Tomioka (NeurIPS, 2023)

What Mechanisms Does Knowledge Distillation Distill? - Cindy Wu; Ekdeep Singh Lubana; Bruno Kacper Mlodozeniec; Robert Kirk; David Krueger 001 (UniReps, 2023)

Meta- (out-of-context) learning in neural networks. - Dmitrii Krasheninnikov; Egor Krasheninnikov; Bruno Mlodozeniec; David Krueger 001 (CoRR, 2023)

Implicitly Bayesian Prediction Rules in Deep Learning. - Bruno Mlodozeniec; David Krueger 001; Richard E. Turner (AABI, 2024)

Implicit meta-learning may lead language models to trust more reliable sources. - Dmitrii Krasheninnikov; Egor Krasheninnikov; Bruno Kacper Mlodozeniec; Tegan Maharaj; David Krueger 001 (ICML, 2024)

A Generative Model of Symmetry Transformations. - James Urquhart Allingham; Bruno Mlodozeniec; Shreyas Padhy; Javier Antorán; David Krueger 001; Richard E. Turner; Eric T. Nalisnick; José Miguel Hernández-Lobato (NeurIPS, 2024)

Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes. - Jihao Andreas Lin; Shreyas Padhy; Bruno Mlodozeniec; Javier Antorán; José Miguel Hernández-Lobato (NeurIPS, 2024)

Denoising Diffusion Probabilistic Models in Six Simple Steps. - Richard E. Turner; Cristiana-Diana Diaconu; Stratis Markou; Aliaksandra Shysheya; Andrew Y. K. Foong; Bruno Mlodozeniec (CoRR, 2024)

Warm Start Marginal Likelihood Optimisation for Iterative Gaussian Processes. - Jihao Andreas Lin; Shreyas Padhy; Bruno Mlodozeniec; José Miguel Hernández-Lobato (CoRR, 2024)

Influence Functions for Scalable Data Attribution in Diffusion Models. - Bruno Kacper Mlodozeniec; Runa Eschenhagen; Juhan Bae; Alexander Immer; David Krueger 001; Richard E. Turner (ICLR, 2025)

Distributional Training Data Attribution. - Bruno Mlodozeniec; Isaac Reid; Sam Power; David Krueger 001; Murat A. Erdogdu; Richard E. Turner; Roger B. Grosse (CoRR, 2025)