| A full-stack view of probabilistic computing with p-bits: devices, architectures and algorithms S Chowdhury, A Grimaldi, NA Aadit, S Niazi, M Mohseni, S Kanai, H Ohno, ... IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2023 | 31 | 2023 |
| Training deep Boltzmann networks with sparse Ising machines S Niazi, NA Aadit, M Mohseni, S Chowdhury, Y Qin, KY Camsari arXiv preprint arXiv:2303.10728, 2023 | 12 | 2023 |
| CMOS+ stochastic nanomagnets: heterogeneous computers for probabilistic inference and learning NS Singh, K Kobayashi, Q Cao, K Selcuk, T Hu, S Niazi, NA Aadit, ... arXiv preprint arXiv:2304.05949, 2023 | 6 | 2023 |
| CMOS plus stochastic nanomagnets enabling heterogeneous computers for probabilistic inference and learning NS Singh, K Kobayashi, Q Cao, K Selcuk, T Hu, S Niazi, NA Aadit, ... Nature Communications 15 (1), 2685, 2024 | 1 | 2024 |
| Hardware Demonstration of Feedforward Stochastic Neural Networks with Fast MTJ-based p-bits NS Singh, S Niazi, S Chowdhury, K Selcuk, H Kaneko, K Kobayashi, ... 2023 International Electron Devices Meeting (IEDM), 1-4, 2023 | 1 | 2023 |
| Mean-Field Assisted Deep Boltzmann Learning with Probabilistic Computers S Chowdhury, S Niazi, KY Camsari arXiv preprint arXiv:2401.01996, 2024 | | 2024 |
| CMOS+ stochastic MTJ: Heterogeneous p-computers for energy-based machine learning K Kobayashi, Q Cao, N Singh, K Selcuk, T Hu, S Niazi, N Aadit, S Kanai, ... APS March Meeting Abstracts 2023, Y54. 005, 2023 | | 2023 |
Kerem Y ÇamsarıUniversity of California, Santa BarbaraVerified email at ucsb.edu
