Contact: Arnout Devos
Using prior knowledge, Few-Shot Learning aims to (rapidly) generalize to new tasks containing only a few samples of information.
We have multiple possible projects available around this topic, which we're happy to discuss once you reach out (email@example.com).
An example of a few-shot learning semester project in our group from Spring 2020:
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification
Research work from our group in relation to few-shot learning:
Regression Networks for Meta-Learning Few-Shot Classification
Reproducing Meta-learning with differentiable closed-form solvers