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30 results found

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

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

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

Dataset of channels and received IEEE 802.11ay signals for sensing applications in the 60GHz band

Data provided by  National Institute of Standards and Technology

The dataset can be used to develop and test algorithms for communication and sensing in the 60GHz band. The dataset consists of synthetically generated indoor mm-wave channels between a MIMO transmitter and a MIMO receivers. Multiple targets are moving in the room. Number of targets, velocity of each target and trajectory are randomized across the dataset. The dataset contains also noisy received IEEE 802.11ay channel estimation fields. The dataset is suitable for development and testing of machine/deep learning algorithms.

Tags: Sensing,communication,millimeter wave,dataset,machine learning,deep learning,channel model,IEEE 802.11ay,IEEE 802.11bf,

Modified: 2024-02-22

Views: 0

**SUPERSEDED** Software and Data for Modeling OFDM Communication Signals with Generative Adversarial Networks

Data provided by  National Institute of Standards and Technology

This software and data have been superseded. Please visit https://doi.org/10.18434/mds2-2532

Tags: generative adversarial network,machine learning,wireless communications,

Modified: 2024-02-22

Views: 0

Data Supporting "Seabird Tissue Archival and Monitoring Project (STAMP) Data from 1999-2010"

Data provided by  National Institute of Standards and Technology

Here we provide curated analytical chemistry data for eggs collected from 1999 to 2010 on a subset of species and analytes that were measured regularly and reasonably systematically. Included in this publication are 487 samples analyzed for 174 ubiquitous environmental contaminants such as (poly)brominated diphenyl ethers (BDEs), mercury, organochlorine pesticides (OCPs), and polychlorinated biphenyls (PCBs). Data were collated to form a dataset useful in chemometric and related analyses of the marine ecosystem in the north Pacific Ocean.

Tags: NIST Biorepository,eggs,tissues,BDEs,PBDEs,PCBs,Pesticides,mercury,trace elements,heavy metals,organic,inorganic,chemistry,stable isotopes,genetics,Environment and Climate,chemometric,machine learning,ML,seabird,bird,Pacific Ocean,

Modified: 2024-02-22

Views: 0

ANDiE: the Autonomous Neutron Diffraction Explorer.

Data provided by  National Institute of Standards and Technology

ANDiE the Autonomous Neutron Diffraction Explorer is a tool for autonomously discovering the magnetic transition temperature and transition dynamics of a material from neutron diffraction experiments. The Jupyter notebooks used to implement ANDiE can be found here: https://github.com/usnistgov/ANDiE-v1_0 The Jupyter notebooks contained therein are of ANDiE as implemented at the WAND2 instrument at the HB-2C beamline at the High-Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL).

Tags: Autonomous Experiments,neutron diffraction,machine learning,Active Learning,Artificial Intelligence,

Modified: 2024-02-22

Views: 0