5 citations · 12 across the 8 of their papers we have counts for
6 papers · 1 filter
EMoE: Eigenbasis-Guided Routing for Mixture-of-Experts
Anzhe Cheng, Shukai Duan, Shixuan Li +5
The relentless scaling of deep learning models has led to unsustainable computational demands, positioning Mixture-of-Experts (MoE) architectures as a promising path towards greate…
Neuro-Inspired Information-Theoretic Hierarchical Perception for Multimodal Learning
Xiongye Xiao, Gengshuo Liu, Gaurav Gupta +6
Integrating and processing information from various sources or modalities are critical for obtaining a comprehensive and accurate perception of the real world in autonomous systems…
Unlocking Deep Learning: A BP-Free Approach for Parallel Block-Wise Training of Neural Networks
Anzhe Cheng, Zhenkun Wang, Chenzhong Yin +5
Backpropagation (BP) has been a successful optimization technique for deep learning models. However, its limitations, such as backward- and update-locking, and its biological impla…
Leader-Follower Neural Networks with Local Error Signals Inspired by Complex Collectives
Chenzhong Yin, Mingxi Cheng, Xiongye Xiao +4
The collective behavior of a network with heterogeneous, resource-limited information processing units (e.g., group of fish, flock of birds, or network of neurons) demonstrates hig…
Neuro-Inspired Hierarchical Multimodal Learning
Xiongye Xiao, Gengshuo Liu, Gaurav Gupta +6
Integrating and processing information from various sources or modalities are critical for obtaining a comprehensive and accurate perception of the real world. Drawing inspiration…
Fractional dynamics foster deep learning of COPD stage prediction
Chenzhong Yin, Mihai Udrescu, Gaurav Gupta +6
Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death worldwide. Current COPD diagnosis (i.e., spirometry) could be unreliable because the test depends…