Non-parametric Representation Learning with Kernels. - Pascal Mattia Esser; Maximilian Fleissner; Debarghya Ghoshdastidar (AAAI, 2024)

Explaining Kernel Clustering via Decision Trees. - Maximilian Fleissner; Leena Chennuru Vankadara; Debarghya Ghoshdastidar (ICLR, 2024)

Decision Trees for Interpretable Clusters in Mixture Models and Deep Representations. - Maximilian Fleissner; Maedeh Zarvandi; Debarghya Ghoshdastidar (CoRR, 2024)

Data Augmentations Go Beyond Encoding Invariances: A Theoretical Study on Self-Supervised Learning. - Shlomo Libo Feigin; Maximilian Fleissner; Debarghya Ghoshdastidar (CoRR, 2024)

Infinite Width Limits of Self Supervised Neural Networks. - Maximilian Fleissner; Gautham Govind Anil; Debarghya Ghoshdastidar (AISTATS, 2025)

A Probabilistic Model for Self-Supervised Learning. - Maximilian Fleissner; Pascal Mattia Esser; Debarghya Ghoshdastidar (CoRR, 2025)

Impact of Bottleneck Layers and Skip Connections on the Generalization of Linear Denoising Autoencoders. - Jonghyun Ham; Maximilian Fleissner; Debarghya Ghoshdastidar (CoRR, 2025)