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Trojan Detection Software Challenge - cyber-pdf-dec2022-train
Data provided by National Institute of Standards and Technology
Round 12 Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of pdf malware classification AIs trained Contaigio dataset feature vectors. 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. This dataset consists of 120 AI models using a small set of model architectures.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
Trojan Detection Software Challenge - image-classification-sep2022-train
Data provided by National Institute of Standards and Technology
Round 11 Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of image classification AIs trained on synthetic image data build from Cityscapes. 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. This dataset consists of 288 AI models using a small set of model architectures.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
analphipy: A python package to analyze pair-potential metrics.
Data provided by National Institute of Standards and Technology
`analphipy` is a python package to calculate metrics for classical models for pair potentials. It provides a simple and extendable api for pair potentials creation. Several routines to calculate metrics are included in the package. The main features of `analphipy` are 1) Pre-defined spherically symmetric potentials. 2) Simple interface to extended to user defined pair potentials. 3) Routines to calculate Noro-Frenkel effective parameters. 4) Routines to calculate Jensen-Shannon divergence.
Tags: python,statistical mechanics,
Modified: 2024-02-22
Views: 0
CyRSoXS: A GPU-accelerated virtual instrument for Polarized Resonant Soft X-ray Scattering (P-RSoXS)
Data provided by National Institute of Standards and Technology
Polarized Resonant Soft X-ray scattering (P-RSoXS) has emerged as a powerful synchrotron-based tool to measure structure in complex, chemically heterogeneous systems. P-RSoXS combines principles of X-ray scattering and X-ray spectroscopy; this combination provides unique sensitivity to molecular orientation and chemical heterogeneity in soft materials such as polymers and biomaterials.
Tags: polymer,python,C++,CUDA,polymer nanocomposite,polymer solution,X-ray scattering,software,tool,computation,
Modified: 2024-02-22
Views: 0
tmmc-lnpy: A python package to analyze Transition Matrix Monte Carlo lnPi data.
Data provided by National Institute of Standards and Technology
A python package to analyze ``lnPi`` data from Transition Matrix Monte Carlo(TMMC) simulation. The main output from TMMC simulations, ``lnPi``, provides a means to calculate a host of thermodynamicproperties. Moreover, if ``lnPi`` is calculated at a specific chemical potential, it can be reweighted to providethermodynamic information at a different chemical potential. The python package``tmmc-lnpy`` provides a wide array of routines to analyze ``lnPi`` data.
Tags: python,molecular simulation,data analysis,Transition Matrix Monte Carlo,statistical mechanics,
Modified: 2024-02-22
Views: 0
FCpy: Feldman-Cousins Confidence Interval Calculator
Data provided by National Institute of Standards and Technology
Python scripts and Python+Qt graphical user interface for calculating Feldman-Cousins confidence intervals for low-count Poisson processes in the presence of a known background and for Gaussian processes with a physical lower limit of 0.
Tags: python,SIMS,statistics,mass spectrometry,Confidence Interval,CI,Feldman,Cousins,Poisson,Gaussian,
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
Trojan Detection Software Challenge - object-detection-jul2022-train
Data provided by National Institute of Standards and Technology
Round 10 Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of object detection AIs trained on the COCO dataset. 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. This dataset consists of 144 AI models using a small set of model architectures.
Tags: Trojan Detection; Artificial Intelligence; AI; Machine Learning; Adversarial Machine Learning;,
Modified: 2024-02-22
Views: 0
Entropy Source Validation Client
Data provided by National Institute of Standards and Technology
This tool is a Python client that can interact with the NIST Entropy Source Validation Test System.
Tags: python,Entropy Source Validation Test System,NIST,CMVP,ESV Client,
Modified: 2024-02-22
Views: 0