KSD Aggregated Goodness-of-fit Test. - Antonin Schrab; Benjamin Guedj; Arthur Gretton (NeurIPS, 2022)

Efficient Aggregated Kernel Tests using Incomplete $U$-statistics. - Antonin Schrab; Ilmun Kim; Benjamin Guedj; Arthur Gretton (NeurIPS, 2022)

Discussion of 'Multiscale Fisher's Independence Test for Multivariate Dependence'. - Antonin Schrab; Wittawat Jitkrittum; Zoltán Szabó 001; Dino Sejdinovic; Arthur Gretton (CoRR, 2022)

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

Differentially Private Permutation Tests: Applications to Kernel Methods. - Ilmun Kim; Antonin Schrab (CoRR, 2023)

MMD Aggregated Two-Sample Test. - Antonin Schrab; Ilmun Kim; Mélisande Albert; Béatrice Laurent; Benjamin Guedj; Arthur Gretton (J. Mach. Learn. Res., 2023)

Practical Kernel Tests of Conditional Independence. - Roman Pogodin; Antonin Schrab; Yazhe Li; Danica J. Sutherland; Arthur Gretton (CoRR, 2024)

Credal Two-Sample Tests of Epistemic Ignorance. - Siu Lun Chau; Antonin Schrab; Arthur Gretton; Dino Sejdinovic; Krikamol Muandet (CoRR, 2024)

Credal Two-Sample Tests of Epistemic Uncertainty. - Siu Lun Chau; Antonin Schrab; Arthur Gretton; Dino Sejdinovic; Krikamol Muandet (AISTATS, 2025)

Robust Kernel Hypothesis Testing under Data Corruption. - Antonin Schrab; Ilmun Kim (AISTATS, 2025)

A Practical Introduction to Kernel Discrepancies: MMD, HSIC & KSD. - Antonin Schrab (CoRR, 2025)

A Unified View of Optimal Kernel Hypothesis Testing. - Antonin Schrab (CoRR, 2025)