2 citations · 2 across the 2 of their papers we have counts for
3 papers · 1 filter
Learning Commute-Time-Preserving World Models for Planning
Michael Hauri, Peter Buttaroni, Fabian A. Mikulasch +1
World models allow agents to plan in latent space by choosing a sequence of actions that most reduces the distance to a given goal state. Thus, planning can benefit from latent rep…
Predictive Self-Supervised Learning Provably Identifies Stochastic Signals under Nuisance
Fabian A. Mikulasch, Friedemann Zenke
Self-supervised learning (SSL) by predicting in latent space, without generating the input data itself, learns highly abstract, useful representations. Intuitively, this success is…
Understanding Self-Supervised Learning via Latent Distribution Matching
Fabian A Mikulasch, Friedemann Zenke
Self-supervised learning (SSL) excels at finding general-purpose latent representations from complex data, yet lacks a unifying theoretical framework that explains the diverse exis…