3 citations · 6 across the 4 of their papers we have counts for
4 papers
Near-Optimal Learning of Local Lindbladians
Itai Arad, Zhili Chen, Naixu Guo +2
We study the problem of learning local Lindbladians from black-box access to the physical evolution, where the goal is to estimate all Hamiltonian and dissipative coefficients. For…
Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought
Tencent Hunyuan Team, Ao Liu, Botong Zhou +248
As Large Language Models (LLMs) rapidly advance, we introduce Hunyuan-TurboS, a novel large hybrid Transformer-Mamba Mixture of Experts (MoE) model. It synergistically combines Mam…
Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers
Yuxuan Du, Xinbiao Wang, Naixu Guo +6
This tutorial intends to introduce readers with a background in AI to quantum machine learning (QML) -- a rapidly evolving field that seeks to leverage the power of quantum compute…
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…