4 papers
Rethinking Prediction Horizons: Decoupling Model Queries from State Updates in Few-Step MeanFlow
Tinglan Wang, Haixu Liu, Shaobo Chen +4
MeanFlow predicts interval-average velocities, but conventional few-step sampling ties the interval queried from the model to the duration of the state update. We separate these tw…
Kaiwu-PyTorch-Plugin: Bridging Deep Learning and Photonic Quantum Computing for Energy-Based Models and Active Sample Selection
Hongdong Zhu, Qi Gao, Yin Ma +6
This paper introduces the Kaiwu-PyTorch-Plugin (KPP) to bridge Deep Learning and Photonic Quantum Computing across multiple dimensions. KPP integrates the Coherent Ising Machine in…
A versatile coherent Ising computing platform
Hai Wei, Chengjun Ai, Putuo Guo +12
Coherent Ising Machines (CIMs) have emerged as a hybrid form of quantum computing devices designed to solve NP-complete problems, offering an exciting opportunity for discovering o…
Quantum-Boosted High-Fidelity Deep Learning
Feng-ao Wang, Shaobo Chen, Yao Xuan +12
A fundamental limitation of probabilistic deep learning is its predominant reliance on Gaussian priors. This simplistic assumption prevents models from accurately capturing the com…