A curated list of resources for Document Understanding (DU) topic

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

A set of Deep Reinforcement Learning Agents implemented in Tensorflow.

A new one shot face swap approach for image and video domains.

Efficient, scalable and enterprise-grade CPU/GPU inference server for Hugging Face transformer models.

Gluon CV Toolkit

In this work, we proposed a two-stage framework, which produces debiased representations by using a fairness constraint adversarial framework in the first stage.

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.

Practical recommendations for mitigating bias in automated speaker recognition, and outline future research directions.

Repository of algorithmic bias related metrics and measures to enable researchers and practitioners to leverage their use. The repository is also intended to allow researchers to expand their research to identify more metrics that may be relevant and appropriate to specific context.

This bias detection tool identifies potentially unfairly treated groups of similar users by a binary algorithmic classifier. The tool identifies clusters of users that face a higher misclassification rate compared to the rest of the data set. Clustering is an unsupervised ML method, so no data is needed is required on protected attributes of users. The metric by which bias is defined can be manually chosen in advance: False Negative Rate (FNR), False Positive Rate (FPR), or Accuracy (Acc).

Intersectional Fairness (ISF) is a bias detection and mitigation technology developed by Fujitsu for intersectional bias, which is caused by the combinations of multiple protected attributes. ISF is hosted as an open source project by the Linux Foundation.

Zero-trust 360 RAIAAS platform for audit and certification of enterprise-wide AI solutions using trust indicators following ethical standards

Automate, simplify, and streamline your end-to-end AI risk management process.

Biaslyze is a python package that helps to get started with the analysis of bias within NLP models and offers a concrete entry point for further impact assessments and mitigation measures.

PAM is the contextual bias detection solution for AI and ML models. Achieve trustworthiness by identifying hidden bias prior to launching and improving explainability. Get a socio-technical bias analysis within minutes to validate your solution pre-market and ensure compliance with AI regulations.

Multi-VALUE is a suite of resources for evaluating and achieving English dialect invariance.

QuantPi’s platform unites AI testing with AI governance. It is the cockpit of AI-first organizations to collaborate on – to efficiently and responsibly understand, enhance and steer their individual AI models as well as their complete AI landscape.

Use a model inventory and AI Factsheets as part of your AI Governance strategy to track the lifecycles of machine learning models from training to production. View factsheets for model assets that track lineage events and facilitate efficient ModelOps governance.

Justifai is an AI platform enabling business users to build trustworthy AI solutions fast, cost-effective and with minimal compliance risks