4 papers
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…
EEGDM: Learning EEG Representation with Latent Diffusion Model
Shaocong Wang, Tong Liu, Yihan Li +6
Recent advances in self-supervised learning for EEG representation have largely relied on masked reconstruction, where models are trained to recover randomly masked signal segments…
Memory-guided Prototypical Co-occurrence Learning for Mixed Emotion Recognition
Ming Li, Yong-Jin Liu, Fang Liu +6
Emotion recognition from multi-modal physiological and behavioral signals plays a pivotal role in affective computing, yet most existing models remain constrained to the prediction…
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…