Data set from peer-reviewed publication: A. J. Fleisher et al., Absolute 13C/12C Isotope Amount Ratio for Vienna Pee Dee Belemnite from Infrared Absorption Spectroscopy, Nature Physics. Measurements of isotope ratios are predominantly made with reference to standard specimens that have been characterized in the past. In the 1950s, the carbon isotope ratio was referenced to a belemnite sample collected by Heinz Lowenstam and Harold Urey in South Carolina?s Pee Dee region.

Round 4 Test DatasetThe data being generated and disseminated is the test 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.

Round 4 Holdout DatasetThe data being generated and disseminated is the holdout 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.

Round 5 Train DatasetThe data being generated and disseminated is the train data used to construct trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform text sentiment classification on English text. 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.

Round 5 Test DatasetThis is the test data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform text sentiment classification on English text. 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.

Round 5 Holdout DatasetThis is the holdout data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform text sentiment classification on English text. 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.

Round 6 Train DatasetThis is the training data used to construct and evaluate trojan detection software solutions. This data, generated at NIST, consists of natural language processing (NLP) AIs trained to perform text sentiment classification on English text. 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.

Hourly observations of carbon dioxide (CO2) and methane (CH4) mole fractions in dry air from tower- and rooftop-based sites in the Los Angeles Megacity Carbon Project network. Carbon monoxide (CO) observations exist at several stations in this network but are not included in this data release pending additional calibration verification. Please contact the authors for higher frequency data, which are available on request. Data files are comma delimited (CSV). Measurements of each species may be from two or more different heights above ground.

This repository contains two types of datasets: 4D-STEM data collected from a thermal annealing series of P3MEEMT films. 4D-STEM data:Dose series: Collected from P3MEEMT film annealed at 115 C. Each HDF5 file was generated from the raw data using the fpdpy software package to reshape and embed metadata. No other preprocessing was performed. Annealing series: Collected from P3MEEMT films annealed at 75 C, 115 C, 145 C, and 175 C. Each temperature contains two sets of 4D-STEM data collected at low and high magnification.

Round rl-lavaworld-jul2023-train Train DatasetThis is the training data used to create and evaluate trojan detection software solutions. This data, generated at NIST, consists of Reinforcement Learning agents trained to navigate the Lavaworld Minigrid environment. 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.