67 citations · 68 across the 5 of their papers we have counts for
5 papers
Energy-Efficient Supervised Learning with a Binary Stochastic Forward-Forward Algorithm
Risi Jaiswal, Supriyo Datta, Joseph G. Makin
Reducing energy consumption has become a pressing need for modern machine learning, which has achieved many of its most impressive results by scaling to larger and more energy-cons…
Improving deep neural network performance through sampling
Lakshmi A. Ghantasala, Ming-Che Li, Risi Jaiswal +4
Energy efficient sampling with probabilistic neurons or p-bits has been demonstrated in the context of Boltzmann machines and it is natural to ask if these approaches can be extend…
An Efficient MCMC Approach to Energy Function Optimization in Protein Structure Prediction
Lakshmi A. Ghantasala, Risi Jaiswal, Supriyo Datta
Protein structure prediction is a critical problem linked to drug design, mutation detection, and protein synthesis, among other applications. To this end, evolutionary data has be…
Benchmarking a Probabilistic Coprocessor
Jan Kaiser, Risi Jaiswal, Behtash Behin-Aein +1
Computation in the past decades has been driven by deterministic computers based on classical deterministic bits. Recently, alternative computing paradigms and domain-based computi…
Autonomous Probabilistic Coprocessing with Petaflips per Second
Brian Sutton, Rafatul Faria, Lakshmi A. Ghantasala +3
In this paper we present a concrete design for a probabilistic (p-) computer based on a network of p-bits, robust classical entities fluctuating between -1 and +1, with probabiliti…