Zobrazeno 1 - 10
of 2 013
pro vyhledávání: '"Ding, Zhao"'
We propose the characteristic generator, a novel one-step generative model that combines the efficiency of sampling in Generative Adversarial Networks (GANs) with the stable performance of flow-based models. Our model is driven by characteristics, al
Externí odkaz:
http://arxiv.org/abs/2405.05512
We introduce an ordinary differential equation (ODE) based deep generative method for learning conditional distributions, named Conditional F\"ollmer Flow. Starting from a standard Gaussian distribution, the proposed flow could approximate the target
Externí odkaz:
http://arxiv.org/abs/2402.01460
We propose SDORE, a semi-supervised deep Sobolev regressor, for the nonparametric estimation of the underlying regression function and its gradient. SDORE employs deep neural networks to minimize empirical risk with gradient norm regularization, allo
Externí odkaz:
http://arxiv.org/abs/2401.04535
We introduce a novel unit-time ordinary differential equation (ODE) flow called the preconditioned F\"{o}llmer flow, which efficiently transforms a Gaussian measure into a desired target measure at time 1. To discretize the flow, we apply Euler's met
Externí odkaz:
http://arxiv.org/abs/2311.03660
Autor:
Ding Zhao, Jiangkun Fan, Zesen Chen, Wenyuan Zhang, Zhixin Zhang, Bin Tang, Jian Wang, Hongchao Kou, Jinshan Li
Publikováno v:
Journal of Materials Research and Technology, Vol 32, Iss , Pp 3750-3762 (2024)
In the continuous cooling process, the growth of the equiaxed α-phase grains in near-α high-temperature titanium alloys is controlled by the diffusion of alloying elements. Establishing a specific connection between the cooling rate and the diffusi
Externí odkaz:
https://doaj.org/article/ef8775d0618f4aa6ba3dde241a37ce98
Autor:
Yu-zhi XIE, Peng WANG, Huan-huan DONG, Rui-xiang WANG, Fu-cheng ZHANG, Hang-xin YU, Yi-ding ZHAO, Yong-xiang ZHANG, Wen-kun ZHU, Tao CHEN
Publikováno v:
He huaxue yu fangshe huaxue, Vol 46, Iss 4, Pp 345-357 (2024)
With the rapid development of nuclear energy, uranium as the main element of nuclear energy production, its source has been widely explored. At present, uranium resources mainly come from uranium mining, and a lot of radioactive uranium containing wa
Externí odkaz:
https://doaj.org/article/3466aa5bf4774a3f82d4e07ab3ee31ad
Publikováno v:
ICML 2023, workshop on Data-centric Machine Learning Research
The prevalent use of benchmarks in current offline reinforcement learning (RL) research has led to a neglect of the imbalance of real-world dataset distributions in the development of models. The real-world offline RL dataset is often imbalanced over
Externí odkaz:
http://arxiv.org/abs/2307.02752
Publikováno v:
精准医学杂志, Vol 39, Iss 3, Pp 203-208 (2024)
Objective To investigate the effect and mechanism of TGF-β on macrophage-derived cancer-associated fibroblasts (CAFs) in bladder cancer tissue. Methods The Kaplan-Meier method was used to investigate the relationship between the expression of α-SMA
Externí odkaz:
https://doaj.org/article/5de616c086ba4258b105b15dd4b444fd
Tailoring texture in a near-α titanium alloy: Insights from strain paths and cooling rate influences
Autor:
Jiangkun Fan, Ding Zhao, Zesen Chen, Zhixin Zhang, Jing Wang, Bin Tang, Zhiyong Chen, Qingjiang Wang, Hongchao Kou, Jinshan Li
Publikováno v:
Journal of Materials Research and Technology, Vol 30, Iss , Pp 1388-1402 (2024)
By elucidating the progressive relationship from the rolling stress state to the activation of slip systems and then to lattice rotation, this paper clarifies the influence mechanism of strain paths on the evolution of α-phase texture in near-α tit
Externí odkaz:
https://doaj.org/article/71a89baafaf14587ac63ed4f15eade4d
Publikováno v:
Case Studies in Thermal Engineering, Vol 61, Iss , Pp 104995- (2024)
Thermal management plays a crucial role in the performance of electronic devices. For devices operating at room temperatures, manifold microchannels (MMCs) are essential for heat dissipation in heat sinks due to their low thermal resistance and press
Externí odkaz:
https://doaj.org/article/ba45a214188c440faa14dfcdd5d566a3