4 citations · 14 across the 12 of their papers we have counts for
3 papers · 1 filter
CN101 - A Digital Thermodynamic Computer for Generative AI
Lars Holdijk, Denis Melanson, Zier Mensch +14
Thermodynamic computing is an emerging hardware paradigm, in which stochastic physical dynamics serve as the direct computational primitive. The recent explosion of generative AI h…
Robust Stochastic Gradient Posterior Sampling with Lattice Based Discretisation
Zier Mensch, Lars Holdijk, Samuel Duffield +4
Stochastic-gradient MCMC methods enable scalable Bayesian posterior sampling but often suffer from sensitivity to minibatch size and gradient noise. To address this, we propose Sto…
Energy-Time-Accuracy Tradeoffs in Thermodynamic Computing
Alberto Rolandi, Paolo Abiuso, Patryk Lipka-Bartosik +3
In the paradigm of thermodynamic computing, instead of behaving deterministically, hardware undergoes a stochastic process in order to sample from a distribution of interest. While…