Author

Yixin Wang

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Book Open access Sep 2026

CONSEQUENCES '26 — The 5th Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems

Real-world embodiments of recommender systems are increasingly often posed as decision-making systems, imposing consequences on the world around them. The literature on causal and counterfactual inference allows us to reason about these consequences, and better understand their implications. Whilst this research area h...

Olivier Jeunen, Harrie Oosterhuis, Flavian Vasile et al. · Proceedings of the 20th ACM... · 0 citations

Jul 2026

Adapting Evidential Neural Networks to Test-Time Neighbor Fusion Improves Molecular Property Prediction

A trained molecular property model can be refined at test time by correcting each prediction with the measured labels of the most similar training molecules, a retraining-free procedure we call neighbor fusion; evidential neural networks make it principled by using their aleatoric and epistemic uncertainty to parameter...

Cameron Gruich, Yao Weichi, Yixin Wang et al. · arXiv.org · 0 citations