1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
Probabilistic Abduction for Visual Abstract Reasoning via Learning Rules in Vector-symbolic Architectures
Michael Hersche, Francesco di Stefano, Thomas Hofmann +2
Abstract reasoning is a cornerstone of human intelligence, and replicating it with artificial intelligence (AI) presents an ongoing challenge. This study focuses on efficiently sol…
cs.LG2023
Unified machine learning tasks and datasets for enhancing renewable energy
Arsam Aryandoust, Thomas Rigoni, Francesco di Stefano +1
Multi-tasking machine learning (ML) models exhibit prediction abilities in domains with little to no training data available (few-shot and zero-shot learning). Over-parameterized M…