noobasuna

GENCDA

Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery

Recognition-and-Classification-of-Facial-Attributes

Created a classifier that can identify and classify 41 types of facial attributes, using an ImageNet pre-trained ResNext50 model provided by PyTorch and CelebA dataset. Multiple data augmentation techniques were used along with the MSE loss function. Obtained a training accuracy of 95.7% and test accuracy of 91.8%.

counterfactual-benchmark

Benchmark study of quality and faithfulness of counterfactual image generation

GazeTR

The codes and models in 'Gaze Estimation using Transformer, ICPR2022'.

capybara_dataset

This is a dataset composed of images of capybaras to be used for training a model for object detection

GazeCapture

Eye Tracking for Everyone

stage

PyTorch implementation of STAGE model

colmap

COLMAP - Structure-from-Motion and Multi-View Stereo

Andrew-NG-Notes

This is Andrew NG Coursera Handwritten Notes.

L2CS-Net

The official PyTorch implementation of L2CS-Net for gaze estimation and tracking

causica

face-alignment

:fire: 2D and 3D Face alignment library build using pytorch

IALS

[IJCAI 2021] Disentangled Face Attribute Editing via Instance-Aware Latent Space Search

AIX360

Interpretability and explainability of data and machine learning models

FLAME_PyTorch

This is a implementation of the 3D FLAME model in PyTorch

Deep3DFaceReconstruction

3DMM-Fitting-Pytorch

A 3DMM fitting framework using Pytorch.

SFAMNet

SFAMNet: A Scene Flow Attention-based Micro-expression Network

Facial-Prior-Based-FOMM

[ACM MM'21] Facial Prior Based First Order Motion Model for Micro-expression Generation

DiCE

Generate Diverse Counterfactual Explanations for any machine learning model.

MiVOLO

MiVOLO age & gender transformer neural network

ICPy

This packages provides a simple python implementation of Invariant Causal Prediction (ICP)

ges

Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search" by David Maxwell Chickering.

aicp

Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", by Juan L Gamella and Christina Heinze-Deml.

InvariantCausalPrediction.jl

Invariant Causal Prediction in pure Julia

icp

Python implementation of the Invariant Causal Prediction (ICP) algorithm, from the 2015 paper "Causal inference using invariant prediction: identification and confidence intervals" by Jonas Peters, Peter Bühlmann and Nicolai Meinshausen.

MIRACLE

Causal-Discovery-from-Nonstationary-Heterogeneous-Data

Causal Discovery from Nonstationary/Heterogeneous Data.

GIN-Condition-for-Estimating-Latent-Variable-Causal-Graphs

Generalized Independent Noise Condition for Latent Causal Structure

Heterogeneous-Effects

Machine Learning and Heterogeneous Effects taught by Brigham Frandsen