no code implementations • 11 May 2023 • Jing Zhao, Heliang Zheng, Chaoyue Wang, Long Lan, Wanrong Huang, Wenjing Yang
Specifically, we proposed two disturbance methods, i. e., Rollback disturbance (Back-D) and Image disturbance (Image-D), to construct misalignment between the noisy images used for predicting null-text guidance and text guidance (subsequently referred to as \textbf{null-text noisy image} and \textbf{text noisy image} respectively) in the sampling process.
no code implementations • 7 Jun 2022 • Jinkai Tian, Xiaoyu Sun, Yuxuan Du, Shanshan Zhao, Qing Liu, Kaining Zhang, Wei Yi, Wanrong Huang, Chaoyue Wang, Xingyao Wu, Min-Hsiu Hsieh, Tongliang Liu, Wenjing Yang, DaCheng Tao
Due to the intrinsic probabilistic nature of quantum mechanics, it is reasonable to postulate that quantum generative learning models (QGLMs) may surpass their classical counterparts.
no code implementations • 29 Sep 2021 • Jiateng Huang, Wanrong Huang, Long Lan, Dan Wu
In this paper, we propose a meta attention method for state-based reinforcement learning tasks, which combines attention mechanism and meta-learning based on the Off-Policy Actor-Critic framework.