😎 A curated list of awesome MLOps tools

Python implementation for evaluating explanations presented in "On the (In)fidelity and Sensitivity for Explanations" in NeurIPS 2019 for evaluating any saliency explanations.

Pretrained TorchVision models on CIFAR10 dataset (with weights)

reference implementation for "explanations can be manipulated and geometry is to blame"

💡 Adversarial attacks on explanations and how to defend them

Implementation of the BReG-NeXt architecture

Model interpretability and understanding for PyTorch

A simple tool to update bib entries with their official information (e.g., DBLP or the ACL anthology).

Lime: Explaining the predictions of any machine learning classifier

👮 Logs all imported packages and their versions

Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)

When significant neurons of trained neural networks is dropped gradually, the trained model loses it ability to classify the label correctly.

Expw cleaned dataset for facial expression recognition

Efficient Facial Feature Learning with Wide Ensemble-based Convolutional Neural Networks

PyTorch Face Recognizer based on 'VGGFace2: A dataset for recognising faces across pose and age'

Pretrained Pytorch face detection (MTCNN) and facial recognition (InceptionResnet) models

Top conferences & Journals focused on Facial expression recognition (FER)/ Facial action unit (FAU)

A curated list of awesome Fairness in AI resources

A simple bias guideline for data scientists.

Facial Expression Editing with Controllable Expression Intensity

Clean Code in Python, published by Packt

Pytorch implementation of SIREN - Implicit Neural Representations with Periodic Activation Function

Morphing and Sampling Network for Dense Point Cloud Completion (AAAI2020)

Semantic3D segmentation with Open3D and PointNet++

A facial expression classification system that recognizes 6 basic emotions: happy, sad, surprise, fear, anger and neutral.

Realtime application framework (Node.JS server)

JavaScript 3D Library.