6 papers
Drift and Dependence: Layer-wise Information-Theoretic Bounds for Replay-Based Continual Learning
Tieliang Gong, Zhongbo Zhang, Wen Wen +1
Continual learning must absorb new tasks without erasing old ones, and replay---mixing a small buffer of past examples into current training---is among the most effective remedies…
Controlled Dynamics Attractor Transformer
Cheng Zhang, Minnan Luo, Zesheng Yang +3
Transformer architectures have dramatically advanced representation learning and inference in deep models through self-attention mechanisms. In parallel,associative memory (AM) fra…
SpecXMaster Technical Report
Yutang Ge, Yaning Cui, Hanzheng Li +15
Intelligent spectroscopy serves as a pivotal element in AI-driven closed-loop scientific discovery, functioning as the critical bridge between matter structure and artificial intel…
Information-Theoretic Generalization Bounds of Replay-based Continual Learning
Wen Wen, Tieliang Gong, Zeyu Gao +3
Continual learning (CL) has emerged as a dominant paradigm for acquiring knowledge from sequential tasks while avoiding catastrophic forgetting. Although many CL methods have been…
Unsupervised Structural Scene Decomposition via Foreground-Aware Slot Attention with Pseudo-Mask Guidance
Huankun Sheng, Ming Li, Yixiang Wei +4
Recent advances in object-centric representation learning have shown that slot attention-based methods can effectively decompose visual scenes into object slot representations with…
A Unified Information-Theoretic Framework for Meta-Learning Generalization
Wen Wen, Tieliang Gong, Yuxin Dong +2
In recent years, information-theoretic generalization bounds have gained increasing attention for analyzing the generalization capabilities of meta-learning algorithms. However, ex…