3 papers
cs.AI2026
Advantage-Guided Diffusion for Model-Based Reinforcement Learning
Daniele Foffano, Arvid Eriksson, David Broman +2
Model-based reinforcement learning (MBRL) with autoregressive world models suffers from compounding errors, whereas diffusion world models mitigate this by generating trajectory se…
cs.AI2026
Learning to Rank the Initial Branching Order of SAT Solvers
Arvid Eriksson, Gabriel Poesia, Roman Bresson +2
Finding good branching orders is key to solving SAT problems efficiently, but finding such branching orders is a difficult problem. Using a learning based approach to predict a goo…
cs.CV2025
Reproducibility review of "Why Not Other Classes": Towards Class-Contrastive Back-Propagation Explanations
Arvid Eriksson, Anton Israelsson, Mattias Kallhauge
"Why Not Other Classes?": Towards Class-Contrastive Back-Propagation Explanations (Wang & Wang, 2022) provides a method for contrastively explaining why a certain class in a neural…