44 citations · 104 across the 11 of their papers we have counts for
11 papers
Uncertainty Quantification in Working Memory via Moment Neural Networks
Hengyuan Ma, Wenlian Lu, Jianfeng Feng
Humans possess a finely tuned sense of uncertainty that helps anticipate potential errors, vital for adaptive behavior and survival. However, the underlying neural mechanisms remai…
Efficient Combinatorial Optimization via Heat Diffusion
Hengyuan Ma, Wenlian Lu, Jianfeng Feng
Combinatorial optimization problems are widespread but inherently challenging due to their discrete nature. The primary limitation of existing methods is that they can only access…
Probabilistic computation and uncertainty quantification with emerging covariance
Hengyuan Ma, Yang Qi, Li Zhang +2
Building robust, interpretable, and secure AI system requires quantifying and representing uncertainty under a probabilistic perspective to mimic human cognitive abilities. However…
Preconditioned Score-based Generative Models
Hengyuan Ma, Xiatian Zhu, Jianfeng Feng +1
Score-based generative models (SGMs) have recently emerged as a promising class of generative models. However, a fundamental limitation is that their sampling process is slow due t…
Self-organization of nonlinearly coupled neural fluctuations into synergistic population codes
Hengyuan Ma, Yang Qi, Pulin Gong +3
Neural activity in the brain exhibits correlated fluctuations that may strongly influence the properties of neural population coding. However, how such correlated neural fluctuatio…
Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling
Hengyuan Ma, Li Zhang, Xiatian Zhu +1
Score-based generative models (SGMs) have recently emerged as a promising class of generative models. However, a fundamental limitation is that their inference is very slow due to…