10 citations · 14 across the 5 of their papers we have counts for
6 papers
Probabilistic Algorithms for Ising Machines from Optimization to Generative AI
Corentin Delacour, Xiuqi Zhang, Abdelrahman S. Abdelrahman +4
Ising machines have emerged as promising hardware accelerators for intractable optimization and sampling problems, yet their practical impact increasingly hinges on the co-design o…
Spin Vector Control for Heisenberg-Inspired Probabilistic Computing
Yuanqiu Tan, Rahul Tripathi, Saleh Bunaiyan +5
Probabilistic bits (p-bits) have emerged as a cornerstone of probabilistic computing, enabling energy-efficient hardware implementation for probabilistic inference and combinatoria…
Programmable Probabilistic Computer with 1,000,000 p-bits
Navid Anjum Aadit, Xiuqi Zhang, Shuvro Chowdhury +10
Probabilistic computers built from p-bits have been proposed as hardware accelerators for sampling and optimizing Ising models, but existing systems have been confined to a single…
IsingFormer: Augmenting Parallel Tempering With Learned Proposals
Saleh Bunaiyan, Corentin Delacour, Shuvro Chowdhury +3
Generative models have been extensively used to accelerate MCMC mixing for sampling and optimization, but their effective integration with standard MCMC remains an open question. H…
Connecting physics to systems with modular spin-circuits
Kemal Selcuk, Saleh Bunaiyan, Nihal Sanjay Singh +5
An emerging paradigm in modern electronics is that of CMOS + requiring the integration of standard CMOS technology with novel materials and technologies denoted by .…
Heisenberg machines with programmable spin-circuits
Saleh Bunaiyan, Supriyo Datta, Kerem Y. Camsari
We show that we can harness two recent experimental developments to build a compact hardware emulator for the classical Heisenberg model in statistical physics. The first is the de…