1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2022
Robust Meta-Representation Learning via Global Label Inference and Classification
Ruohan Wang, Isak Falk, Massimiliano Pontil +1
Few-shot learning (FSL) is a central problem in meta-learning, where learners must efficiently learn from few labeled examples. Within FSL, feature pre-training has recently become…
cs.LG2020★ 1 cited
GENNI: Visualising the Geometry of Equivalences for Neural Network Identifiability
Daniel Lengyel, Janith Petangoda, Isak Falk +5
We propose an efficient algorithm to visualise symmetries in neural networks. Typically, models are defined with respect to a parameter space, where non-equal parameters can produc…