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REMI: Resource for Materials Informatics
Data provided by National Institute of Standards and Technology
The REsource for Materials Informatics (REMI) will host a diverse collection of scripting notebooks (Jupyter, Matlab LiveScripts, etc.) for collecting, pre-processing, analyzing, and visualizing materials data. Notebooks are curated using tags aligned to Materials Science and Data Science topics. REMI emerged from the realization that both experts and novices wanted examples of using machine learning for science. Meanwhile, lots of experts are developing digital notebooks (e.g. Jupyter) to demonstrate step-by-step data collection, pre-processing, analysis and visualization.
Tags: machine learning,data analysis,data processing,materials science,materials genome initiative,
Modified: 2024-02-22
Views: 0
NIST DART-MS Forensics Database (is-CID)
Data provided by National Institute of Standards and Technology
The NIST DART-MS Forensics Database is an evaluated collection of in-source collisionally-induced dissociation (is-CID) mass spectra of compounds of interest to the forensics community (e.g. seized drugs, cutting agents, etc.). The is-CID mass spectra were collected using Direct Analysis in Real-Time (DART) Mass Spectrometry (MS), either by NIST scientists or by contributing agencies noted per compound. The database is provided as a general-purpose structure data file (.SDF).
Tags: Standard reference data,mass spectra,Ion Fragmentation,mass spectrometry,NIST Mass Spectral Libraries,Chemical Identification,Biosciences and Health,Security and Forensics,
Modified: 2024-02-22
Views: 0
Trojan Detection Software Challenge - image-classification-dec2020-train
Data provided by National Institute of Standards and Technology
Round 3 Training DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
Trojan Detection Software Challenge - image-classification-aug2020-test
Data provided by National Institute of Standards and Technology
Round 2 Test DatasetThe data being generated and disseminated is the test data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform a variety of tasks (image classification, natural language processing, etc.). A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
Trojan Detection Software Challenge - image-classification-aug2020-holdout
Data provided by National Institute of Standards and Technology
Round 2 Holdout DatasetThe data being generated and disseminated is the holdout data used to evaluate trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform a variety of tasks (image classification, natural language processing, etc.). A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
Trojan Detection Software Challenge - image-classification-dec2020-test
Data provided by National Institute of Standards and Technology
Round 3 Test DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
Trojan Detection Software Challenge - image-classification-dec2020-holdout
Data provided by National Institute of Standards and Technology
Round 3 Holdout DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
Trojan Detection Software Challenge - image-classification-feb2021-train
Data provided by National Institute of Standards and Technology
Round 4 Train DatasetThe data being generated and disseminated is the training data used to construct trojan detection software solutions. This data, generated at NIST, consists of human level AIs trained to perform image classification. A known percentage of these trained AI models have been poisoned with a known trigger which induces incorrect behavior. This data will be used to develop software solutions for detecting which trained AI models have been poisoned via embedded triggers.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
Dark solitons in BECs dataset 2.0
Data provided by National Institute of Standards and Technology
Atomic Bose-Einstein condensates (BECs) are widely investigated systems that exhibit quantum phenomena on a macroscopic scale. For example, they can be manipulated to contain solitonic excitations including conventional solitons, vortices, and many more. Broadly speaking, solitonic excitations are solitary waves that retain their size and shape and often propagate at a constant speed. They are present in many systems, at scales ranging from microscopic, to terrestrial and even astronomical.
Tags: machine learning,Bose-Einstein condensates,dark solitons,
Modified: 2024-02-22
Views: 0
Dataset from HDX-MS Studies of IgG1 Glycoforms and Their Interactions with the Fc(gamma)RIa (CD64) Receptor
Data provided by National Institute of Standards and Technology
This database gives hydrogen-deuterium exchange mass spectrometry (HDX-MS) data from measurements of three purified IgG1 glycoform samples, predominantly G0F, G2F, and SAF, in isolation and in complexation with the high-affinity receptor, Fc(gamma)RIa (CD64). The IgG1 antibody used in this study, aIL8hFc, is a murine-human chimeric IgG1, which inhibits IL-8 binding to human neutrophils.
Tags: antibody-receptor interaction,chromatography,HDX-MS,hydrogen-deuterium exchange,glycosylation,mass spectrometry,monoclonal antibody,precision,peptide,protein,proteolysis,proteomics,receptor.,
Modified: 2024-02-22
Views: 0