New paper from the lab led by Fabian Mikulasch. 📄 https://arxiv.org/abs/2609.37789 🌐 https://info-ldm.github.io/ Code: https://github.com/fmi-basel/identifiable-stochastic-nuisance Why does predicting in latent space (JEPA, CPC, SimCLR…) work so well on messy data, with changing lighting, camera angles,Continue reading
Tag: fabian
The Lab at the Bernstein Conference
Like every year, the lab is excited to attend and present at the Bernstein Conference and Satellite workshops. Workshop talks Monday 28th, 15:05-15:35 (room 3.104) Rory will give the talk “Connectome-constrained spiking network models ofContinue reading
Paper: Understanding Self-Supervised Learning via Latent Distribution Matching
Fabian’s paper “Understanding Self-Supervised Learning via Latent Distribution Matching” was accepted as ICML spotlight! https://arxiv.org/abs/2605.03517 We unify self-supervised learning (SSL) algorithms (e.g., contrastive, VICReg, stopgrad) via latent distribution matching (LDM), which matches an induced latentContinue reading