1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2026
Towards Identifiable Representations under Misspecified Structure
Yuke Li, Yujia Zheng, Ziyi Chen +2
The presence of noise that depends on the latent variables poses a fundamental challenge to identifiability. Existing results rely on conditional independence among the observation…
cs.LG2025
Understanding Catastrophic Interference: On the Identifibility of Latent Representations
Yuke Li, Yujia Zheng, Tianyi Xiong +2
Catastrophic interference, also known as catastrophic forgetting, is a fundamental challenge in machine learning, where a trained learning model progressively loses performance on…
cs.CV2024★ 1 cited
Cross-Modal Few-Shot Learning: a Generative Transfer Learning Framework
Zhengwei Yang, Yuke Li, Qiang Sun +3
Most existing studies on few-shot learning focus on unimodal settings, where models are trained to generalize to unseen data using a limited amount of labeled examples from a singl…