4 citations · 6 across the 10 of their papers we have counts for
3 papers · 1 filter
Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks
Alfredo Reichlin, Gustaf Tegnér, Miguel Vasco +3
Given a finite set of sample points, meta-learning algorithms aim to learn an optimal adaptation strategy for new, unseen tasks. Often, this data can be ambiguous as it might belon…
Model-based reinforcement learning for protein backbone design
Frederic Renard, Cyprien Courtot, Alfredo Reichlin +1
Designing protein nanomaterials of predefined shape and characteristics has the potential to dramatically impact the medical industry. Machine learning (ML) has proven successful i…
Goal-Conditioned Reinforcement Learning from Sub-Optimal Data on Metric Spaces
Alfredo Reichlin, Miguel Vasco, Hang Yin +1
We study the problem of learning optimal behavior from sub-optimal datasets for goal-conditioned offline reinforcement learning under sparse rewards, invertible actions and determi…