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
Tag: ssl
The lab at NeurIPS 2023
We’re at NeurIPS with two papers this year. If you are in New Orleans, come to see us! Dis-inhibitory neuronal circuits can control the sign of synaptic plasticity. Rossbroich, J. and Zenke, F. (2023) doi:Continue reading
Paper: Implicit variance regularization in non-contrastive SSL
New paper from the lab accepted at NeurIPS: “Implicit variance regularization in non-contrastive SSL.” In our article, first-authored by Manu and Axel, we add further understanding to how non-contrastive self-supervised learning (SSL) methods avoid collapse.Continue reading