123 citations · 515 across the 7 of their papers we have counts for
7 papers
Probabilistic computing with p-bits
Jan Kaiser, Supriyo Datta
Digital computers store information in the form of bits that can take on one of two values 0 and 1, while quantum computers are based on qubits that are described by a complex wave…
Hardware-aware Boltzmann machine learning using stochastic magnetic tunnel junctions
Jan Kaiser, William A. Borders, Kerem Y. Camsari +3
One of the big challenges of current electronics is the design and implementation of hardware neural networks that perform fast and energy-efficient machine learning. Spintronics i…
Demonstration of nanosecond operation in stochastic magnetic tunnel junctions
Christopher Safranski, Jan Kaiser, Philip Trouilloud +3
Magnetic tunnel junctions operating in the superparamagnetic regime are promising devices in the field of probabilistic computing, which is suitable for applications like high-dime…
Hardware Design for Autonomous Bayesian Networks
Rafatul Faria, Jan Kaiser, Kerem Y. Camsari +1
Directed acyclic graphs or Bayesian networks that are popular in many AI related sectors for probabilistic inference and causal reasoning can be mapped to probabilistic circuits bu…
Probabilistic Circuits for Autonomous Learning: A simulation study
Jan Kaiser, Rafatul Faria, Kerem Y. Camsari +1
Modern machine learning is based on powerful algorithms running on digital computing platforms and there is great interest in accelerating the learning process and making it more e…
Subnanosecond Fluctuations in Low-Barrier Nanomagnets
Jan Kaiser, Avinash Rustagi, Kerem Y. Camsari +3
Fast magnetic fluctuations due to thermal torques have useful technological functionality ranging from cryptography to probabilistic computing. The characteristic time of fluctuati…