Zobrazeno 1 - 10
of 1 465
pro vyhledávání: '"Lu, Cong"'
In many real-world settings, an agent must learn to act in environments where no reward signal can be specified, but a set of expert demonstrations is available. Imitation learning (IL) is a popular framework for learning policies from such demonstra
Externí odkaz:
http://arxiv.org/abs/2407.00495
Go-Explore is a powerful family of algorithms designed to solve hard-exploration problems, built on the principle of archiving discovered states, and iteratively returning to and exploring from the most promising states. This approach has led to supe
Externí odkaz:
http://arxiv.org/abs/2405.15143
Autor:
Gupta, Gunshi, Yadav, Karmesh, Gal, Yarin, Batra, Dhruv, Kira, Zsolt, Lu, Cong, Rudner, Tim G. J.
Embodied AI agents require a fine-grained understanding of the physical world mediated through visual and language inputs. Such capabilities are difficult to learn solely from task-specific data. This has led to the emergence of pre-trained vision-la
Externí odkaz:
http://arxiv.org/abs/2405.05852
Diffusion generative models have recently become a robust technique for producing and modifying coherent, high-quality video. This survey offers a systematic overview of critical elements of diffusion models for video generation, covering application
Externí odkaz:
http://arxiv.org/abs/2405.03150
Autor:
Jackson, Matthew Thomas, Matthews, Michael Tryfan, Lu, Cong, Ellis, Benjamin, Whiteson, Shimon, Foerster, Jakob
In many real-world settings, agents must learn from an offline dataset gathered by some prior behavior policy. Such a setting naturally leads to distribution shift between the behavior policy and the target policy being trained - requiring policy con
Externí odkaz:
http://arxiv.org/abs/2404.06356
Autor:
Deng, Cheng-Lin, Liu, Yu, Zhang, Yu-Ran, Li, Xue-Gang, Liu, Tao, Chen, Chi-Tong, Liu, Tong, Lu, Cong-Wei, Wang, Yong-Yi, Li, Tian-Ming, Fang, Cai-Ping, Zhou, Si-Yun, Song, Jia-Cheng, Xu, Yue-Shan, He, Yang, Liu, Zheng-He, Huang, Kai-Xuan, Xiang, Zhong-Cheng, Wang, Jie-Ci, Zheng, Dong-Ning, Xue, Guang-Ming, Xu, Kai, Yu, H. F., Fan, Heng
High-order topological phases of matter refer to the systems of $n$-dimensional bulk with the topology of $m$-th order, exhibiting $(n-m)$-dimensional boundary modes and can be characterized by topological pumping. Here, we experimentally demonstrate
Externí odkaz:
http://arxiv.org/abs/2402.16070
Offline reinforcement learning aims to enable agents to be trained from pre-collected datasets, however, this comes with the added challenge of estimating the value of behavior not covered in the dataset. Model-based methods offer a solution by allow
Externí odkaz:
http://arxiv.org/abs/2402.12527
Autor:
Liu, Di, Maimaitijiang, Remina, Gu, Jing, Zhong, Shuyi, Zhou, Mengping, Wu, Ziyue, Luo, Ao, Lu, Cong, Hao, Yuantao
Publikováno v:
JMIR mHealth and uHealth, Vol 7, Iss 9, p e13127 (2019)
BackgroundMany university students are lacking adequate physical exercise and are failing to develop physical activity (PA) behaviors in China. PA app use could improve this situation. ObjectiveThe aim of this study was to use the unified theory of
Externí odkaz:
https://doaj.org/article/24042dad06db4323a01892003cb1a4dc
Publikováno v:
Phys. Rev. A 109, 042623 (2024)
Quantum metrology explores quantum effects to improve the measurement accuracy of some physical quantities beyond the classical limit. However, due to the interaction between the system and the environment, the decoherence can significantly reduce th
Externí odkaz:
http://arxiv.org/abs/2311.14020
Publikováno v:
Ann. Phys. (Berlin) 535, 2300138 (2023)
Due to the long coherence time and efficient manipulation, the surface electron (SE) provides a perfect two-dimensional platform for quantum computation and quantum simulation. In this work, a theoretical scheme to realize the controlled-NOT (CNOT) g
Externí odkaz:
http://arxiv.org/abs/2303.08650