AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...
Heterogeneous domain adaptation remains challenging due to the inconsistent feature representations and data distributions between the source and target domains. In this paper, we introduce ...
[2026.03.09] We have updated our technical report with more experimental results. By integrating contrastive, self-supervised, and reconstruction learning, we have trained numerous visual tokenizers ...
Oracle Bone Inscriptions (OBI), the earliest systematic writing in China, are crucial for understanding early Chinese civilization. However, many inscriptions remain undeciphered due to limited data, ...
Pain, a pervasive global health concern, affects a large segment of population worldwide. Accurate pain assessment remains a challenge due to the limitations of conventional self-report scales, which ...
The recent breakthroughs of Large Language Models (LLMs) in the context of natural language processing have opened the way to significant advances in protein research. Indeed, the relationships ...
2021 NeurIPS Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection 2021 NeurIPS Exploring the Limits of Out-of-Distribution Detection 2021 NeurIPS Locally Most ...
Abstract: Bottleneck problems are an important class of optimization problems that have recently gained increasing attention in the domain of machine learning and information theory. They are widely ...
Abstract: This paper proposes a novel adversarial scheme for learning from data under harsh learning conditions of partially labelled samples and skewed class distributions. This novel scheme ...
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