Python Graph-networks Resources

Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!

keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o

Energy-based GFlowNets Code for Generative Flow Networks for Discrete Probabilistic Modeling by Dinghuai Zhang, Nikolay Malkin, Zhen Liu, Alexandra Vo

Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks

LabGraph is a a Python-first framework used to build sophisticated research systems with real-time streaming, graph API, and parallelism.

Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.

Iterative refinement graph neural network for antibody sequence-structure co-des

GraphNLI: A Graph-based Natural Language Inference Model for Polarity Prediction in Online Debates Vibhor Agarwal, Sagar Joglekar, Anthony P. Young an

Equivariant Subgraph Aggregation Networks (ESAN) This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (IC

traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to

Hatchet Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data. It is intended for analyzing

DIR-GNN "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)

Live Demo (currently not running, on it) Espial is an engine for automated organization and discovery in knowledge bases. It can be adapted to run wit

Cite our paper if you find this project useful https://www.ijariit.com/manuscripts/v7i4/V7I4-1139.pdf Abstract Image processing technology is used in

TorchGRL TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffi

NLP - Movie review sentiment analysis The colab notebook contains the code for building a LSTM Recurrent Neural Network that gives 87-88% accuracy on

GNN_PPI Codes and models for the paper "Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction". Lear

1st place solution in CCF BDCI 2021 ULSEG challenge This is the source code of the 1st place solution for ultrasound image angioma segmentation task (

machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be

Explaining Deep Neural Networks - A comparison of different CAM methods based on an insect data set This is the repository for the Deep Learning proje

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap

Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss

Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. Code, based on the PyTorch framework, for reprodu

CoINN: Correlated-informed neural networks: a new machine learning framework to predict pressure drop in micro-channels Accurate pressure drop estimat

Global-Local Path Networks for Monocular Depth Estimation with Vertical CutDepth [Paper] Downloads [Downloads] Trained ckpt files for NYU Depth V2 and

Sparse network learning with snlpy Very large and sparse networks appear often in the wild and present unique algorithmic opportunities and challenges

GAN-based Matrix Factorization for Recommender Systems This repository contains the datasets' splits, the source code of the experiments and their res

GenGNN: A Generic FPGA Framework for Graph Neural Network Acceleration Stefan Abi-Karam*, Yuqi He*, Rishov Sarkar*, Lakshmi Sathidevi, Zihang Qiao, Co

Approximate Multiplier by HEAM What's HEAM? HEAM is a general optimization method to generate high-efficiency approximate multipliers for specific app

This repository contains the scripts needed to generate the results from the paper Unity Propagation in Bayesian Networks Handling Inconsistency via U

Dual-Contrastive-Learning A PyTorch implementation for our paper "Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation". Y

On the adaptation of recurrent neural networks for system identification This repository contains the Python code to reproduce the results of the pape

Leaf: Multiple-Choice Question Generation Easy to use and understand multiple-choice question generation algorithm using T5 Transformers. The applicat

This repo holds the codes of our paper: Adaptive Dropblock Enhanced GenerativeAdversarial Networks for Hyperspectral Image Classification, which is ac

AttentionHTR PyTorch implementation of an end-to-end Handwritten Text Recognition (HTR) system based on attention encoder-decoder networks. Scene Text

OntoProtein This is the implement of the paper "OntoProtein: Protein Pretraining With Ontology Embedding". OntoProtein is an effective method that mak

Neural Architecture Search for Spiking Neural Networks Pytorch implementation code for [Neural Architecture Search for Spiking Neural Networks] (https

On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic

GNDC For submission to IEEE TKDE. Overview Here we provide the implementation of GND-Nets (Graph Neural Diffusion Networks) in TensorFlow. The reposit

Author Name Disambiguation with Knowledge Graph Embeddings using Literals This is the repository for the master thesis project on Knowledge Graph Embe

This is part of the code to reproduce the results of the paper Do Neural Networks for Segmentation Understand Insideness? [pdf] by K. Villalobos (*),

Explanatory Learning This is the official repository for "Explanatory Learning: Beyond Empiricism in Neural Networks". Datasets Download the datasets

Momentum Capsule Network Official implementation of the paper Momentum Capsule Networks (MoCapsNet). Abstract Capsule networks are a class of neural n

Post-training Quantization for Neural Networks with Provable Guarantees Authors: Jinjie Zhang ([email protected]), Yixuan Zhou ([email protected]) and Ray

This is a Kaggle competition in which we have to identify if the given lesion image is malignant or not for Melanoma which is a type of skin cancer.

What can linearized neural networks actually say about generalization? This is the source code to reproduce the experiments of the NeurIPS 2021 paper

GreaseLM: Graph REASoning Enhanced Language Models This repo provides the source code & data of our paper "GreaseLM: Graph REASoning Enhanced Language

TGRNet: A Table Graph Reconstruction Network for Table Structure Recognition Xue, Wenyuan, et al. "TGRNet: A Table Graph Reconstruction Network for Ta

Noether Networks: meta-learning useful conserved quantities This repository contains the code necessary to reproduce experiments from "Noether Network

Why Spectral Normalization Stabilizes GANs: Analysis and Improvements [paper (NeurIPS 2021)] [paper (arXiv)] [code] Authors: Zinan Lin, Vyas Sekar, Gi

STAR_KGC This repo contains the source code of the paper accepted by WWW'2021. "Structure-Augmented Text Representation Learning for Efficient Knowled

CSKG: The CommonSense Knowledge Graph CSKG is a commonsense knowledge graph that combines seven popular sources into a consolidated representation: AT

Graph Analysis From Scratch Goal In this notebook we wanted to implement some functionalities to analyze a weighted graph only by using algorithms imp

Roam to Logseq The script loads a json export of a Roam graph and cleans it up f

This repo supplements our Survey on Transformers in Medical Imaging Fahad Shamshad, Salman Khan, Syed Waqas Zamir, Muhammad Haris Khan, Munawar Hayat,

Awesome Semantic Segmentation List of awesome things around semantic segmentation 🎉 Semantic segmentation is a computer vision task in which we label

Introduction This repository contains the modified caffe library and network architectures for our paper "Automated Melanoma Recognition in Dermoscopy

Lung Segmentation (2D) Repository features UNet inspired architecture used for segmenting lungs on chest X-Ray images. Demo See the application of the

Cascaded-FCN This repository contains the pre-trained models for a Cascaded-FCN in caffe and tensorflow that segments the liver and its lesions out of

Using Convolutional Neural Networks (CNN) for Semantic Segmentation of Breast Cancer Lesions (BRCA). Master's thesis documents. Bibliography, experiments and reports.

This is an implementation of Volodymyr Mnih's dissertation methods on his Massachusetts road & building dataset and my original methods that are publi

self-driving-car In this repository I will share the source code of all the projects of Udacity Self-Driving Car Engineer Nanodegree. Hope this might

Build status: master (production branch): develop (development branch): Welcome to the CN24 GitHub repository! CN24 is a complete semantic segmentatio

Segment axon and myelin from microscopy data using deep learning. Written in Python. Using the TensorFlow framework. Based on a convolutional neural network architecture. Pixels are classified as either axon, myelin or background.

[CVPR19] DeepCO3: Deep Instance Co-segmentation by Co-peak Search and Co-saliency (Oral paper) Authors: Kuang-Jui Hsu, Yen-Yu Lin, Yung-Yu Chuang PDF:

Built a deep neural network (DNN) that functions as an end-to-end machine translation pipeline. The pipeline accepts english text as input and returns the French translation.

Example-CNN-Project This is a simple project showing how to implement deep neural networks using CNN algorithm. The dataset is taken from this link: h

On Evaluation Metrics for Graph Generative Models Authors: Rylee Thompson, Boris Knyazev, Elahe Ghalebi, Jungtaek Kim, Graham Taylor This is the offic

Disaster Classificiation using CNNs bunnysaini/Disaster-Classificiation Goal To prepare an image processing model to classify the type of disaster bas

News Headlines Generator bunnysaini/Generate-Headlines Goal This project aims to generate news headlines using a Long Short-Term Memory (LSTM) neural

GPU implementation of kNN and SNN GPU implementation of $k$-Nearest Neighbors and Shared-Nearest Neighbors Supported by numba cuda and faiss library E

An ongoing curated collection of awesome software, libraries, frameworks, talks & videos, best practices, learning tutorials and important practical resources about networking in cybersecurity

Multi-modal Text Recognition Networks: Interactive Enhancements between Visual and Semantic Features | paper | Official PyTorch implementation for Mul

Sentiment Analyzer The goal of this project is to perform sentiment analysis on textual data that people generally post on websites like social networ

TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow (Google's Deep Learning framework) with breakpoints + real-time visualization of the data flowing through the computational graph.

nn_builder lets you build neural networks with less boilerplate code. You specify the type of network you want and it builds it. Install pip install n

Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm

Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently This repository is the official implementat

Google AI Open Images - Object Detection Track: Open Solution This is an open solution to the Google AI Open Images - Object Detection Track 😃 More c

Airbus Ship Detection Challenge This is an open solution to the Airbus Ship Detection Challenge. Our goals We are building entirely open solution to t

Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int

ECLARE ECLARE: Extreme Classification with Label Graph Correlations @InProceedings{Mittal21b, author = "Mittal, A. and Sachdeva, N. and Agrawal

GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,

Biomedical Entity Linking This repo provides the code for the paper BERT might be Overkill: A Tiny but Effective Biomedical Entity Linker based on Res

This code implements the paper, Kim et al. (2021). Imputing Qualitative Attributes for Trip Chains Extracted from Smart Card Data Using a Conditional Generative Adversarial Network. Transportation Research Part C. Under Review.

必要なソフト・パッケージ Python3 Numpy JSON Matplotlib 動作確認環境 MacBook Air M1 Python 3.8.2 (arm64) Numpy 1.22.0 Matplotlib 3.5.1 JSON 2.0.9 使い方 draw_time_histgram(

Can We Find Neurons that Cause Unrealistic Images in Deep Generative Networks? Artifact Detection/Correction - Offcial PyTorch Implementation This rep

Neural Net Image Classifier Employs neural networks to classify images into four categories: ship, automobile, dog or frog Viterbi_1.py uses a classic

Brain-Tumor-Detection A convolutional neural network model built with Tensorflow & Keras to detect brain tumor and its different variants. Data of the

this is a simple artificial neural network model using deep learning and torch-audio to classify cats and dog sounds.

Pytorch Implementation of Augmenting Convolutional networks with attention-based aggregation This is the unofficial PyTorch Implementation of "Augment

GraphMLTutorialNLDL22 Tutorial NLDL22: Introduction to Graph Machine Learning, with Jupyter notebooks This tutorial takes place during the conference

Cross-modal Retrieval using Transformer Encoder Reasoning Networks This project reimplements the idea from "Transformer Reasoning Network for Image-Te

Scene Graph Generation from Natural Language Supervision This repository includes the Pytorch code for our paper "Learning to Generate Scene Graph fro

EfficientWord-Net Hotword detection based on one-shot learning Home assistants require special phrases called hotwords to get activated (eg:"ok google

Pytorch Implementation of Learning Mesh-based Simulation With Graph Networks This is the unofficial implementation of the approach described in the pa

This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe

Effective Use of Transformer Networks for Entity Tracking (EMNLP19) This is a PyTorch implementation of our EMNLP paper on the effectiveness of pre-tr

GCNet for Object Detection By Yue Cao, Jiarui Xu, Stephen Lin, Fangyun Wei, Han Hu. This repo is a official implementation of "GCNet: Non-local Networ

EMANet News The bug in loading the pretrained model is now fixed. I have updated the .pth. To use it, download it again. EMANet-101 gets 80.99 on the