Andrei Bursuc

MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments

2023 · arXiv (Cornell University)

Self-supervised learning can be used for mitigating the greedy needs of Vision Transformer networks for very large fully-annotated datasets. Different classes of self-supervised learning offer representations with either good contextual reasoning properties, e.g., using masked …

Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models

2024

Deep Neural Networks (DNNs) are powerful tools for various computer vision tasks, yet they often struggle with reliable uncertainty quantification — a critical requirement for real-world applications. Bayesian Neural Networks (BNN) are equipped for uncertainty …

Position: Semantic Uncertainty Measures Disagreement, Not Reliability

2026 · HAL (Le Centre pour la Communication Scientifique Directe)

<div> Large Language Models and their multi-modal variants see increasingly rapid adoption and deployment, including in settings where reliability matters. However their uncertainty remains difficult to assess as classic or early token-level approaches cannot deal …