Differentiable PAC-Bayes Objectives with Partially Aggregated Neural Networks. - Felix Biggs; Benjamin Guedj (Entropy, 2021)

On Margins and Derandomisation in PAC-Bayes. - Felix Biggs; Benjamin Guedj (AISTATS, 2022)

Non-Vacuous Generalisation Bounds for Shallow Neural Networks. - Felix Biggs; Benjamin Guedj (ICML, 2022)

On Margins and Generalisation for Voting Classifiers. - Felix Biggs; Valentina Zantedeschi; Benjamin Guedj (NeurIPS, 2022)

A Note on the Efficient Evaluation of PAC-Bayes Bounds. - Felix Biggs (CoRR, 2022)

Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty. - Felix Biggs; Benjamin Guedj (AISTATS, 2023)

MMD-Fuse: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting. - Felix Biggs; Antonin Schrab; Arthur Gretton (NeurIPS, 2023)