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NeurIPS 2026École Normale Supérieure, ParisÉcole Normale SupérieureBayesian & probabilistic methods

Annealing in variational inference mitigates mode collapse: a theoretical study on Gaussian mixtures

Annealing in variational inference prevents Gaussian mixture mode collapse via temperature and rate tradeoffs, with sharp collapse probability formulas extending to neural flows.

Luigi Fogliani, Bruno Loureiro, Marylou Gabrié

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Meta AIFacebookMETAMetaÉcole Normale Supérieure, ParisVision-language models

Boosting Brain-to-Image Decoding with TRIBE v2 Data Augmentation

TRIBE v2 synthetic fMRI augmentation improves brain-to-image decoding by up to 68%, though optimal synthetic-to-real ratios vary by dataset, and synthetic-only training achieves above-chance zero-shot decoding.

Yohann Benchetrit, Marlene Careil, Simon Dahan, Hubert Banville and 2 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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strict 2/5