2 papers
quant-ph2024
Quantum Transformer: Accelerating model inference via quantum linear algebra
Naixu Guo, Zhan Yu, Matthew Choi +5
Powerful generative artificial intelligence from large language models (LLMs) harnesses extensive computational resources for inference. In this work, we investigate the transforme…
quant-ph2023
Learning Restricted Boltzmann Machines with greedy quantum search
Liming Zhao, Aman Agrawal, Patrick Rebentrost
Restricted Boltzmann Machines (RBMs) are widely used probabilistic undirected graphical models with visible and latent nodes, playing an important role in statistics and machine le…