Beyond U: Making Diffusion Models Faster & Lighter. - Sergio Calvo-Ordoñez; Jiahao Huang; Lipei Zhang; Guang Yang 006; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2023)

Partially Stochastic Infinitely Deep Bayesian Neural Networks. - Sergio Calvo-Ordoñez; Matthieu Meunier; Francesco Piatti; Yuantao Shi (ICML, 2024)

Epistemic Uncertainty and Observation Noise with the Neural Tangent Kernel. - Sergio Calvo-Ordoñez; Konstantina Palla; Kamil Ciosek (CoRR, 2024)

The Missing U for Efficient Diffusion Models. - Sergio Calvo-Ordoñez; Chun-Wun Cheng; Jiahao Huang; Lipei Zhang; Guang Yang 006; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (Trans. Mach. Learn. Res., 2024)

Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations. - Richard Bergna; Sergio Calvo-Ordoñez; Felix L. Opolka; Pietro Lio; José Miguel Hernández-Lobato (ICLR, 2025)

Observation Noise and Initialization in Wide Neural Networks. - Sergio Calvo-Ordoñez; Jonathan Plenk; Richard Bergna; Alvaro Cartea; José Miguel Hernández-Lobato; Konstantina Palla; Kamil Ciosek (CoRR, 2025)

Post-Hoc Uncertainty Quantification in Pre-Trained Neural Networks via Activation-Level Gaussian Processes. - Richard Bergna; Stefan Depeweg; Sergio Calvo-Ordoñez; Jonathan Plenk; Alvaro Cartea; José Miguel Hernández-Lobato (CoRR, 2025)

Weighted Conditional Flow Matching. - Sergio Calvo-Ordoñez; Matthieu Meunier; Alvaro Cartea; Christoph Reisinger; Yarin Gal; José Miguel Hernández-Lobato (CoRR, 2025)