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pro vyhledávání: '"Tan, Yiqin"'
Autor:
Luo, Simian, Tan, Yiqin, Patil, Suraj, Gu, Daniel, von Platen, Patrick, Passos, Apolinário, Huang, Longbo, Li, Jian, Zhao, Hang
Latent Consistency Models (LCMs) have achieved impressive performance in accelerating text-to-image generative tasks, producing high-quality images with minimal inference steps. LCMs are distilled from pre-trained latent diffusion models (LDMs), requ
Externí odkaz:
http://arxiv.org/abs/2311.05556
Deep reinforcement learning has achieved remarkable performance in various domains by leveraging deep neural networks for approximating value functions and policies. However, using neural networks to approximate value functions or policy functions st
Externí odkaz:
http://arxiv.org/abs/2310.14009
Latent Diffusion models (LDMs) have achieved remarkable results in synthesizing high-resolution images. However, the iterative sampling process is computationally intensive and leads to slow generation. Inspired by Consistency Models (song et al.), w
Externí odkaz:
http://arxiv.org/abs/2310.04378
Training deep reinforcement learning (DRL) models usually requires high computation costs. Therefore, compressing DRL models possesses immense potential for training acceleration and model deployment. However, existing methods that generate small mod
Externí odkaz:
http://arxiv.org/abs/2205.15043
Autor:
Geng, Yuqing1 (AUTHOR), Tan, Yiqin2 (AUTHOR)
Publikováno v:
Discrete Dynamics in Nature & Society. 4/7/2020, p1-12. 12p.
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