Energy-Based Models (EBMs): 目标为优化一个由Energy-Based Models给出的密度: pθ(x)=e−Eθ(x)∫e−Eθ(x)dx ,其中 Eθ(x) 是一个带参数 θ 的非线性回归函数。 用pθ(x) 去拟合 pdata(x) ,利用最大似然,给出损失函数: L(θ)=Ex∼data[−logpθ(x)] ∇θlogpθ(...
density-estimationenergy-based-modelscore-matchinguai2019score-estimation UpdatedJan 7, 2020 Python Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data generative-modelenergy-based-modelporous-media-flownormalizing-flowphysics-constrainedrevers...
26. Comparative study of the dynamic programming-based and rule-based operation strategies for grid-connected PV-battery systems of office buildings 27. Investigation of proton exchange membrane fuel cell stack with inversely phased wavy flow field design 28. Assessment of the water–energy–carbon ne...
Recently, an ML technique called PCA based on SVD has been used to study the collective flow in relativistic HICs. For the two-particle correlations with the Fourier expansion [166,167,168,169], the event-by-event flow fluctuations have been investigated via PCA, revealing the substructures ...
select article Techno-economic analysis of a modular thermochemical battery for electricity storage based on calcium-looping Research articleAbstract only Techno-economic analysis of a modular thermochemical battery for electricity storage based on calcium-looping C. Ortiz, S. García-Luna, A. Carro, E...
AI generated definition based on:Encyclopedia of Energy,2004 About this page Set alert Chapters and Articles You might find these chapters and articles relevant to this topic. Linking scientific research and energy innovation: A comparison of clean and dirty technologies ...
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treatments through the application of phloretin in two distinct contexts. First, phloretin-based combinations were tested against hepatocellular carcinoma (HCC), where combination 1 involved inhibiting glycolysis with phloretin and gluconeogenesis with sodium meta-arsenite, while combination 2 involved ...
We propose a novel unsupervised multi-scale and multi-semantic normalizing flow model, enhanced with an ensemble of neural networks, to detect anomalies based on their feature distributions. Our model estimates the likelihood of non-defective features, identifying anomalies as out-of-distribution values...
combined the formalism with a DFT-GGA based PES49 that provides a description of the NO neutral and anionic states as well as the diabatic coupling between the two states within a Newns-Anderson Hamiltonian formulation. In comparison to experiment,48,50 they showed that IESH for NO(vi = 15)...