6 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.CV2023★ 1 cited
Multi-Domain Learning with Modulation Adapters
Ekaterina Iakovleva, Karteek Alahari, Jakob Verbeek
Deep convolutional networks are ubiquitous in computer vision, due to their excellent performance across different tasks for various domains. Models are, however, often trained in…
cs.LG2020★ 6 cited
Meta-Learning with Shared Amortized Variational Inference
Ekaterina Iakovleva, Jakob Verbeek, Karteek Alahari
We propose a novel amortized variational inference scheme for an empirical Bayes meta-learning model, where model parameters are treated as latent variables. We learn the prior dis…