14 citations · 16 across the 3 of their papers we have counts for
4 papers
Noise-shaped Sampling and Annealing for Scalable On-the-edge Training of Binary and Ternary AI Models
Zihao Chen, Zhili Xiao, Rui-Jie Zhu +3
The training loss of binary and ternary neural networks, expanded as a multilinear polynomial over the discrete weights, is structurally equivalent to the energy of a hierarchical…
Higher-Order Neuromorphic Ising Machines -- Autoencoders and Fowler-Nordheim Annealers are all you need for Scalability
Faiek Ahsan, Saptarshi Maiti, Zihao Chen +8
We report a higher-order neuromorphic Ising machine that exhibits superior scalability compared to architectures based on quadratization, while also achieving state-of-the-art qual…
ON-OFF Neuromorphic ISING Machines using Fowler-Nordheim Annealers
Zihao Chen, Zhili Xiao, Mahmoud Akl +17
We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using a Fowler-Nordheim quantum mec…
Estimation of Energy-dissipation Lower-bounds for Neuromorphic Learning-in-memory
Zihao Chen, Faiek Ahsan, Johannes Leugering +2
Neuromorphic or neurally-inspired optimizers rely on local but parallel parameter updates to solve problems that range from quadratic programming to Ising machines. An ideal realiz…