3 papers
cs.LG2026
From Independent to Correlated Diffusion: Generalized Generative Modeling with Probabilistic Computers
Nihal Sanjay Singh, Mazdak Mohseni-Rajaee, Shaila Niazi +1
Diffusion models have emerged as a powerful framework for generative tasks in deep learning. They decompose generative modeling into two computational primitives: deterministic neu…
cond-mat.mes-hall2024
Connecting physics to systems with modular spin-circuits
Kemal Selcuk, Saleh Bunaiyan, Nihal Sanjay Singh +5
An emerging paradigm in modern electronics is that of CMOS + requiring the integration of standard CMOS technology with novel materials and technologies denoted by .…
cond-mat.mes-hall2023
CMOS + stochastic nanomagnets: heterogeneous computers for probabilistic inference and learning
Nihal Sanjay Singh, Keito Kobayashi, Qixuan Cao +8
Extending Moore's law by augmenting complementary-metal-oxide semiconductor (CMOS) transistors with emerging nanotechnologies (X) has become increasingly important. One important c…