1 citations · 2 across the 6 of their papers we have counts for
3 papers · 1 filter
Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms
Krunoslav Lehman Pavasovic, Jakob Verbeek, Giulio Biroli +1
Classifier-Free Guidance (CFG) is a widely adopted technique in diffusion and flow-based generative models, enabling high-quality conditional generation. A key theoretical challeng…
Approximate Heavy Tails in Offline (Multi-Pass) Stochastic Gradient Descent
Krunoslav Lehman Pavasovic, Alain Durmus, Umut Simsekli
A recent line of empirical studies has demonstrated that SGD might exhibit a heavy-tailed behavior in practical settings, and the heaviness of the tails might correlate with the ov…
MARS: Meta-Learning as Score Matching in the Function Space
Krunoslav Lehman Pavasovic, Jonas Rothfuss, Andreas Krause
Meta-learning aims to extract useful inductive biases from a set of related datasets. In Bayesian meta-learning, this is typically achieved by constructing a prior distribution ove…