244 citations · 824 across the 56 of their papers we have counts for
4 papers · 1 filter
Enabling Local Editing in Diffusion Models by Joint and Individual Component Analysis
Theodoros Kouzelis, Manos Plitsis, Mihalis A. Nicolaou +1
Recent advances in Diffusion Models (DMs) have led to significant progress in visual synthesis and editing tasks, establishing them as a strong competitor to Generative Adversarial…
Scale Equivariant Graph Metanetworks
Ioannis Kalogeropoulos, Giorgos Bouritsas, Yannis Panagakis
This paper pertains to an emerging machine learning paradigm: learning higher-order functions, i.e. functions whose inputs are functions themselves, $\textit{particularly when thes…
Bridging Mini-Batch and Asymptotic Analysis in Contrastive Learning: From InfoNCE to Kernel-Based Losses
Panagiotis Koromilas, Giorgos Bouritsas, Theodoros Giannakopoulos +2
What do different contrastive learning (CL) losses actually optimize for? Although multiple CL methods have demonstrated remarkable representation learning capabilities, the differ…
Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization
James Oldfield, Markos Georgopoulos, Grigorios G. Chrysos +5
The Mixture of Experts (MoE) paradigm provides a powerful way to decompose dense layers into smaller, modular computations often more amenable to human interpretation, debugging, a…