136 citations · 270 across the 6 of their papers we have counts for
3 papers · 1 filter
Mean-Field Assisted Deep Boltzmann Learning with Probabilistic Computers
Shuvro Chowdhury, Shaila Niazi, Kerem Y. Camsari
Despite their appeal as physics-inspired, energy-based and generative nature, general Boltzmann Machines (BM) are considered intractable to train. This belief led to simplified mod…
A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms
Shuvro Chowdhury, Andrea Grimaldi, Navid Anjum Aadit +9
The transistor celebrated its 75 birthday in 2022. The continued scaling of the transistor defined by Moore's Law continues, albeit at a slower pace. Meanwhile, compu…
Training Deep Boltzmann Networks with Sparse Ising Machines
Shaila Niazi, Navid Anjum Aadit, Masoud Mohseni +3
The slowing down of Moore's law has driven the development of unconventional computing paradigms, such as specialized Ising machines tailored to solve combinatorial optimization pr…