Python Causal-networks Resources

moporgic/TDL2048+ TDL2048+ is a highly optimized temporal difference (TD) learning framework for 2048. Features Many common methods related to 2048 ar

Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF

Python-for-Epidemiologists This repository is an introduction to epidemiology analyses in Python. Additionally, the tutorials for my library zEpid are

FInite volume Neural Network (FINN) This repository contains the PyTorch code for models, training, and testing, and Python code for data generation t

Sharpness-aware Quantization for Deep Neural Networks Recent Update 2021.11.23: We release the source code of SAQ. Setup the environments Clone the re

Introduction The brain is the perfect place to look for inspiration to develop more efficient neural networks. One of the main differences with modern

generalized random forests A pluggable package for forest-based statistical estimation and inference. GRF currently provides non-parametric methods fo

ENN Incubator Collection of in-progress libraries for entity neural networks: Neural Network Architectures for Structured State Entity Gym: Abstractio

Detectron2 trained on PubLayNet dataset This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Det

A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow

HAWQ: Hessian AWare Quantization HAWQ is an advanced quantization library written for PyTorch. HAWQ enables low-precision and mixed-precision uniform

Chord Recognition Demo application The demo application is written in C# with .NETCore. As of July 9, 2020, the only version available is for windows

GLANet The code for Global and Local Alignment Networks for Unpaired Image-to-Image Translation arxiv Framework: visualization results: Getting Starte

lacmus The program for searching through photos from the air of lost people in the forest using Retina Net neural nwtwork. The project is being develo

NBFNet: Neural Bellman-Ford Networks This is the official codebase of the paper Neural Bellman-Ford Networks: A General Graph Neural Network Framework

English | 简体中文 Introduction DeepHawkeye is a library to detect unusual patterns in images using features from pretrained neural networks Reference Pat

Code for Discovering Topics in Long-tailed Corpora with Causal Intervention ACL2021 Findings Usage 0. Prepare environment Requirements: python==3.6 te

networkgen A python module to create random networks using network models Usage $

Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay

PlotNeuralNet Latex code for drawing neural networks for reports and presentation. Have a look into examples to see how they are made. Additionally, l

Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX Foolbox is a Python li

DFL-Colab — DeepFaceLab fork for Google Colab This project provides you IPython Notebook to use DeepFaceLab with Google Colaboratory. You can create y

This repository contains all of the code and software labs for MIT 6.S191: Introduction to Deep Learning! All lecture slides and videos are available

MIT Deep Learning This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress. Tutorial: Deep Learning

What is DeepHyper? DeepHyper is a software package that uses learning, optimization, and parallel computing to automate the design and development of

AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

Learning Causal Semantic Representation for Out-of-Distribution Prediction This repository is the official implementation of "Learning Causal Semantic

sm_content_clustering A Python module for clustering creators of social media content into networks. Currently supports identifying potential networks

Implementing Graph Convolutional Networks and Information Retrieval Mechanisms using pure Python and NumPy

generate-2D-quadrilateral-mesh-with-neural-networks-and-tree-search This repository contains single-threaded TreeMesh code. I'm Hua Tong, a senior stu

counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code

PyTorch reference implementation of "End-to-end optimized image compression with competition of prior distributions" by Benoit Brummer and Christophe

GN-Transformer AST This is the official repository for the paper "GN-Transformer: Fusing AST and Source Code information in Graph Networks". Data Prep

corn-ordinal-neuralnet This repository contains the orginal model code and experiment logs for the paper "Deep Neural Networks for Rank Consistent Ord

TYolov5: A Temporal Yolov5 Detector Based on Quasi-Recurrent Neural Networks for Real-Time Handgun Detection in Video Timely handgun detection is a cr

Fisher Induced Sparse uncHanging (FISH) Mask This repo contains the code for Fisher Induced Sparse uncHanging (FISH) Mask training, from "Training Neu

English | 简体中文 Latest News 2021.10.25 Paper "Docking-based Virtual Screening with Multi-Task Learning" is accepted by BIBM 2021. 2021.07.29 PaddleHeli

Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks This is a Pytorch-Lightning implementation of the paper "Self-s

GemNet: Universal Directional Graph Neural Networks for Molecules Reference implementation in PyTorch of the geometric message passing neural network

TensorFlow GNN This is an early (alpha) release to get community feedback. It's under active development and we may break API compatibility in the fut

alpha-GAN Unofficial pytorch implementation of Rosca, Mihaela, et al. "Variational Approaches for Auto-Encoding Generative Adversarial Networks." arXi

Experimental code for paper: Generative Adversarial Networks as Variational Training of Energy Based Models, under review at ICLR 2017 requirements: T

Unrolled Generative Adversarial Networks Luke Metz, Ben Poole, David Pfau, Jascha Sohl-Dickstein arxiv:1611.02163 This repo contains an example notebo

Stacked Generative Adversarial Networks This repository contains code for the paper "Stacked Generative Adversarial Networks", CVPR 2017. Part of the

Language Generation with Recurrent Generative Adversarial Networks without Pre-training Code for training and evaluation of the model from "Language G

Generating Images with Recurrent Adversarial Networks Python (Theano) implementation of Generating Images with Recurrent Adversarial Networks code pro

First Order Divergence for training GANs This repository contains code accompanying the paper First Order Generative Advesarial Netoworks The majority

Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford, Luke Metz, Soumith Chintala All images in t

CaloGAN Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks. This repository c

Bayesian Generative Adversarial Networks in Tensorflow This repository contains the Tensorflow implementation of the Bayesian GAN by Yunus Saatchi and

AttnGAN Pytorch implementation for reproducing AttnGAN results in the paper AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative

GNet-pose Project Page: http://guanghan.info/projects/guided-fractal/ UPDATE 9/27/2018: Prototxts and model that achieved 93.9Pck on LSP dataset. http

tf-SNDCGAN Tensorflow implementation of the paper "Spectral Normalization for Generative Adversarial Networks" (https://www.researchgate.net/publicati

Adversarial Chess TensorFlow implementation of Style Transfer Generative Adversarial Networks: Learning to Play Chess Differently. Requirements To run

Location-Aware Generative Adversarial Networks (LAGAN) for Physics Synthesis This repository contains all the code used in L. de Oliveira (@lukedeo),

Adversarial Video Generation This project implements a generative adversarial network to predict future frames of video, as detailed in "Deep Multi-Sc

SalGAN: Visual Saliency Prediction with Adversarial Networks Junting Pan Cristian Canton Ferrer Kevin McGuinness Noel O'Connor Jordi Torres Elisa Sayr

cppn-gan-vae tensorflow Train Compositional Pattern Producing Network as a Generative Model, using Generative Adversarial Networks and Variational Aut

MGANs Training & Testing code (torch), pre-trained models and supplementary materials for "Precomputed Real-Time Texture Synthesis with Markovian Gene

Fully Convolutional Refined Auto-Encoding Generative Adversarial Networks for 3D Multi Object Scenes This repository contains the source code for Full

pix2vox [Demonstration video] Sketch-Based 3D Exploration with Stacked Generative Adversarial Networks. Generated samples Single-category generation M

StackGAN Pytorch implementation Inception score evaluation StackGAN-v2-pytorch Tensorflow implementation for reproducing main results in the paper Sta

Neural Photo Editor A simple interface for editing natural photos with generative neural networks. This repository contains code for the paper "Neural

iGAN: Interactive Image Generation via Generative Adversarial Networks Project | Youtube | Paper Recent projects: [pix2pix]: Torch implementation for

IllustrationGAN A simple, clean TensorFlow implementation of Generative Adversarial Networks with a focus on modeling illustrations. Generated Images

zi2zi: Master Chinese Calligraphy with Conditional Adversarial Networks Introduction Learning eastern asian language typefaces with GAN. zi2zi(字到字, me

BEGAN in Tensorflow Tensorflow implementation of BEGAN: Boundary Equilibrium Generative Adversarial Networks. Requirements Python 2.7 or 3.x Pillow tq

Generative Adversarial Networks This repository contains the code and hyperparameters for the paper: "Generative Adversarial Networks." Ian J. Goodfel

Some tentative models that incorporate label propagation to graph neural networks for graph representation learning in nodes, links or graphs.

Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl

tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th

Graph Nets library Graph Nets is DeepMind's library for building graph networks in Tensorflow and Sonnet. Contact [email protected] for comments a

Hummingbird Introduction Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to se

pyclustering is a Python, C++ data mining library (clustering algorithm, oscillatory networks, neural networks). The library provides Python and C++ implementations (C++ pyclustering library) of each algorithm or model. C++ pyclustering library is a part of pyclustering and supported for Linux, Windows and MacOS operating systems.

MiniSom Self Organizing Maps MiniSom is a minimalistic and Numpy based implementation of the Self Organizing Maps (SOM). SOM is a type of Artificial N

Geomstats Code Continuous Integration Code coverage (numpy) Code coverage (autograd, tensorflow, pytorch) Documentation Community NEWS: Geomstats is r

CG3 This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning]. R

Image Quality Assessment using Contrastive Learning Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli and Alan C. Bovik This is the offi

DeepMReye: magnetic resonance-based eye tracking using deep neural networks

SSRL-for-image-classification Semi-supervised Representation Learning for Remote Sensing Image Classification Based on Generative Adversarial Networks

CID3 This is a full-featured Decision Trees and Random Forests learner. It can save trees or forests to disk for later use. It is possible to query tr

Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization This repository contains the source code for the paper (link wi

Generating Band-Limited Adversarial Surfaces Using Neural Networks This is the official repository of the technical report that was published on arXiv

counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code

Fast Axiomatic Attribution for Neural Networks This is the official repository accompanying the NeurIPS 2021 paper: R. Hesse, S. Schaub-Meyer, and S.

HaloGraphNet Predict halo masses from simulations via Graph Neural Networks. Given a dark matter halo and its galaxies, creates a graph with informati

Z-PNN: Zoom Pansharpening Neural Network Pansharpening by convolutional neural networks in the full resolution framework is a deep learning method for

LearningPsychologicalSpaces v0.1: v1.1: v1.2: v1.3: v1.4: v1.5: The code in this repository explores learning a mapping from images to psychological s

Salad Salad is an Open Source Python library to segment tissues into different biologically relevant regions based on Hidden Markov Random Fields. The

time-series-classification Short and long time series classification via convolutional neural networks In this project, we present a novel framework f

NOTE: sktime-dl is currently being updated to work correctly with sktime 0.6, and wwill be fully relaunched over the summer. The plan is Refactor and

Python Causal Impact Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of the R CausalI

Causal Inference 360 A Python package for inferring causal effects from observational data. Description Causal inference analysis enables estimating t

DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc

iNNvestigate neural networks! Table of contents Introduction Installation Usage and Examples More documentation Contributing Releases Introduction In

Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co

EZ-Graph EZ Graph is a GUI that allows users to make and train neural networks without writing a single line of code. Requirements python 3 pandas num

High-resolution networks and Segmentation Transformer for Semantic Segmentation Branches This is the implementation for HRNet + OCR. The PyTroch 1.1 v