A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
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Updated
Dec 10, 2024 - Python
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Interpretability and explainability of data and machine learning models
The prime repository for state-of-the-art Multilingual Question Answering research and development.
Fabric for Deep Learning (FfDL, pronounced fiddle) is a Deep Learning Platform offering TensorFlow, Caffe, PyTorch etc. as a Service on Kubernetes
Library for Semi-Automated Data Science
Regression Transformer (2023; Nature Machine Intelligence)
Knowledge-Aware RL agents with Commonsense Reasoning
Quality Controlled Paraphrase Generation (ACL 2022)
Natural Language (NL) to Linear Temporal Logic (LTL)
Codes for reproducing query-efficient black-box attacks in “AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks” , published at AAAI 2019
Codes for reproducing the black-box adversarial attacks in “ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models,” ACM CCS Workshop on AI-Security, 2017
Codes for reproducing the contrastive explanation in “Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives”
Codes for reproducing the robustness evaluation scores in “Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach,” ICLR 2018
Codes for reproducing the adversarial attacks on image captioning systems in “Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning,” ACL 2018
CROWN: A Neural Network Verification Framework for Networks with General Activation Functions
Intu is a Cognitive Embodiment Middleware for AI on the edge.
A dataset for knowledge base population research using Common Crawl and DBpedia.
Semantic Search for Sustainable Development is experimental code for searching documents for text that "semantically" corresponds to any of the UN's Sustainable development goals/targets. For example, it can be used to mine the national development plan documents of a country and identify pieces of text that correspond to any of the SDGs in orde…
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