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Theory aware Machine Learning (TaML)
Data provided by National Institute of Standards and Technology
A code repository and accompanying data for incorporating imperfect theory into machine learning for improved prediction and explainability. Specifically, it focuses on the case study of the dimensions of a polymer chain in different solvent qualities. Jupyter Notebooks for quickly testing concepts and reproducing figures, as well as source code that computes the mean squared error as a function of dataset size for various machine learning models are included.For additional details on the data, please refer to the README.md associated with the data.
Tags: polymers,machine learning,transfer learning,theory,
Modified: 2024-02-22
Views: 0
SolDet: Solitonic feature detection package
Data provided by National Institute of Standards and Technology
SolDet is an object-oriented package for solitonic feature detection in absorption images of Bose-Einstein condensate. with wider use for cold atom image analysis. Featured with classifier, object detector, and Mexican hat metric methods. Technical details are explained in https://arxiv.org/abs/2111.04881.
Tags: soliton,machine learning,python package,
Modified: 2024-02-22
Views: 0
Software for Evaluating Convolutional Generative Adversarial Networks with Classical Random Process Noise Models
Data provided by National Institute of Standards and Technology
This research software package contains Python code to execute experiments on deep generative modeling of classical random process models for noise time series. Specifically, it includes Pytorch implementations of two generative adversarial network (GAN) models for time series based on convolutational neural networks (CNNs): WaveGAN, a 1-D CNN model, and STFT-GAN, a 2-D CNN model. In addition, there are methods for generating and evaluating noise time series defined several by classical random process models.
Tags: time series,machine learning,band-limited noise,power law noise,shot noise,impulsive noise,colored noise,fractional Gaussian noise,fractional Brownian motion,
Modified: 2024-02-22
Views: 0
Thermodynamic Data from Unpublished Sources to Support the New Reference Equation of State for Carbon Dioxide
Data provided by National Institute of Standards and Technology
During work on the new reference equation of state for carbon dioxide [A.H. Harvey, S.A. Tashkun, R. Hellmann, and E.W. Lemmon, J. Phys. Chem. Ref. Data, in preparation], we obtained unpublished data from several sources. These represent numerical values for data only presented graphically in a publication, or in some cases data not present in the publication at all. With the permission of the authors, we document and deposit these data here so they will be available for future workers.
Tags: CO2,carbon dioxide,thermodynamics,melting,heat capacity,sound speed,vapor pressure,virial coefficients,equation of state,
Modified: 2024-02-22
Views: 0
The effects of advanced spectral line shapes on atmospheric carbon dioxide retrievals
Data provided by National Institute of Standards and Technology
This is the data presented in the figures of the paper "The effects of advanced spectral line shapes on atmospheric carbon dioxide retrievals" published in J. Quant. Spectrosc. Radiat. Transfer at https://doi.org/10.1016/j.jqsrt.2022.108324
Tags: greenhouse gases,carbon dioxide,remote sensing,
Modified: 2024-02-22
Views: 0
Segmentation of lipid nanoparticles from cryogenic electron microscopy images
Data provided by National Institute of Standards and Technology
Lipid nanoparticles (LNPs) were prepared as described (https://doi.org/10.1038/s42003-021-02441-2) using the lipids DLin-KC2-DMA, DSPC, cholesterol, and PEG-DMG2000 at mol ratios of 50:10:38.5:1.5. Four sample types were prepared: LNPs in the presence and absence of RNA, and with LNPs ejected into pH 4 and pH 7.4 buffer after microfluidic assembly. To prepare samples for imaging, 3 ?L of LNP formulation was applied to holey carbon grids (Quantifoil, R3.5/1, 200 mesh copper).
Tags: Lipid Nanoparticle,LNP,cryogenic electron microscopy,CryoEM,machine learning,ai,mRNA,
Modified: 2024-02-22
Views: 0
Thermal Conductivity of Binary Mixtures of 1,1,1,2-Tetrafluoroethane(R-134a), 2,3,3,3-Tetrafluoropropene (R-1234yf), and trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants
Data provided by National Institute of Standards and Technology
Workflow: The data that falls into this category are gathered from a measurement program and are published in the archival literature.
Tags: Advanced Materials,Energy,Environment and Climate,Physical Infrastructure,Safety,Security and Forensics,
Modified: 2024-02-22
Views: 0
Speed of Sound Measurements of Binary Mixtures of Difluoromethane (R-32) with 2,3,3,3-Tetrafluoropropene (R-1234yf) or trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants
Data provided by National Institute of Standards and Technology
Speed of Sound Measurements of Binary Mixtures of Difluoromethane (R-32) with 2,3,3,3-Tetrafluoropropene (R-1234yf) or trans-1,3,3,3-Tetrafluoropropene (R-1234ze(E)) Refrigerants
Tags: Advanced Materials,Energy,Environment and Climate,Physical Infrastructure,Safety,Security and Forensics,
Modified: 2024-02-22
Views: 0
Enriched Citation API (Version 1)
Data provided by United States Patent and Trademark Office
The Enriched Citation API provides the Intellectual Property 5 (IP5 - EPO, JPO, KIPO, CNIPA, and USPTO) and the Public with greater insight into the patent evaluation process. It allows users to quickly view information about which references, or prior art, were cited in specific patent application Office Actions, including: bibliographic information of the reference, the claims that the prior art was cited against, and the relevant sections that the examiner relied upon.
Tags: uspto,ip5,enriched,citation,prior art,office action,claims,machine learning,ai,api,statutes,references,
Modified: 2024-02-22
Views: 0
Enriched Citation API (Version 2)
Data provided by United States Patent and Trademark Office
The Enriched Citation API provides the Intellectual Property 5 (IP5 - EPO, JPO, KIPO, CNIPA, and USPTO) and the Public with greater insight into the patent evaluation process. It allows users to quickly view information about which references, or prior art, were cited in specific patent application Office Actions, including: bibliographic information of the reference, the claims that the prior art was cited against, and the relevant sections that the examiner relied upon.
Tags: uspto,ip5,enriched,citation,prior art,office action,claims,machine learning,ai,api,statutes,references,
Modified: 2024-02-22
Views: 0