4 papers
Exploiting Negative Capacitance for Unconventional Coulomb Engineering
Aravindh Shankar, Pramey Upadhyaya, Supriyo Datta
The many-body ground state of a two-dimensional electron system can be tuned by Coulomb engineering through control of the dielectric environment. However, in conventional dielectr…
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…
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…
Emergent Synaptic Plasticity from Tunable Dynamics of Probabilistic Bits
Sagnik Banerjee, Shiva T. Konakanchi, Supriyo Datta +1
Probabilistic (p-) computing, which leverages the stochasticity of its building blocks (p-bits) to solve a variety of computationally hard problems, has recently emerged as a promi…