These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
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Submitrobuststl
TechnicalKoreaUploaded on Apr 29, 2024Unofficial Implementation of RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series (AAAI 2019)
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yopo-you-only-propagate-once
TechnicalUnited StatesUploaded on Apr 22, 2024Code for our nips19 paper: You Only Propagate Once: Accelerating Adversarial Training Via Maximal Principle
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Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & designsteal-ml
TechnicalUploaded on Apr 2, 2024Model extraction attacks on Machine-Learning-as-a-Service platforms.
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Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & designstock-analysis-engine
TechnicalUploaded on Apr 2, 2024Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/
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Collect & process datatensorflow-course
TechnicalUnited StatesUploaded on Apr 2, 2024:satellite: Simple and ready-to-use tutorials for TensorFlow
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Collect & process dataAIAlpha: Multilayer neural network architecture for stock return prediction
TechnicalUploaded on Dec 15, 2023Use unsupervised and supervised learning to predict stocks.
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Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & designUnsupervised Learning for anomaly detection in options pricing
TechnicalSingaporeUploaded on Dec 15, 2023In this notebook we will explore a machine learning approach to find anomalies in stock options pricing.
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Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & designqdrant
TechnicalGermanyUploaded on Dec 15, 2023Qdrant - High-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
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Mathematical foundation of Reinforcement Learning
TechnicalChinaUploaded on Dec 15, 2023This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."
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Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & designDeep Reinforcement Learning Agents
TechnicalUnited StatesUploaded on Dec 15, 2023A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
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Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & designreinforcement-learning-with-tensorflow
TechnicalUploaded on Dec 15, 2023Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
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Pixel-Perfect Structure-from-Motion
TechnicalSwitzerlandUploaded on Dec 15, 2023Pixel-Perfect Structure-from-Motion with Featuremetric Refinement (ICCV 2021, Best Student Paper Award)
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Verify & validateBuild & interpret modelCollect & process dataPlan & designrobuststl
TechnicalKoreaUploaded on Dec 15, 2023Unofficial Implementation of RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series (AAAI 2019)
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rsmove
TechnicalGermanyUploaded on Dec 15, 2023Remote Sensing for Movement Ecology
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Collect & process dataGluon CV Toolkit
TechnicalUploaded on Dec 11, 2023Gluon CV Toolkit
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Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & designTowards inclusive automatic speech recognition
TechnicalUploaded on Dec 11, 2023 This paper, for the first time, systematically quantifies and finds speech recognition bias against gender, age, regional accents and non-native accents, and investigates the origin of this bias by investigating bias cross-lingually (i.e., Dutch and Mandarin) and for two different SotA ASR architectures (a hybrid DNN-HMM and an attention based end-to-end (E2E) model) through a phoneme error analysis.
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NB Defense
TechnicalEducationalProceduralUnited StatesUploaded on Jun 11, 2023NB Defense is an open source JupyterLab Extension as well as a CLI tool for detecting security issues in Jupyter Notebooks. Issues ranging from detecting leaked PII in your notebook output to detecting vulnerable versions of installed dependencies.
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mlr
TechnicalGermanyUploaded on Jun 8, 2023Machine Learning in R
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Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & designAI Vulnerability Database
TechnicalUnited StatesUploaded on Mar 31, 2023AI Vulnerability Database (AVID) is an open-source knowledge base of failure modes for AI models, datasets, and systems. The goals of AVID are to (1) Build out a functional taxonomy of AI harms across the coordinates of security, ethics, and performance (2) House full-fidelity information (metadata, harm metrics, measurements, benchmarks, and mitigation techniques if any) on harm evaluations (3) Evaluate systems, models, and datasets for specific harms and persist the structured results into a single source of truth.
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Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & designDopamine
TechnicalUploaded on Sep 20, 2022Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
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Operate & monitorDeployVerify & validateBuild & interpret modelCollect & process dataPlan & design
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