1297 Repositories
Python noether-networks Libraries
StyleSwin: Transformer-based GAN for High-resolution Image Generation
StyleSwin This repo is the official implementation of "StyleSwin: Transformer-based GAN for High-resolution Image Generation". By Bowen Zhang, Shuyang
Source Code for AAAI 2022 paper "Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching"
Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching This repository is an official implementation of
A Japanese tokenizer based on recurrent neural networks
Nagisa is a python module for Japanese word segmentation/POS-tagging. It is designed to be a simple and easy-to-use tool. This tool has the following
Source Code for AAAI 2022 paper "Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching"
Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching This repository is an official implementation of
Header-only library for using Keras models in C++.
frugally-deep Use Keras models in C++ with ease Table of contents Introduction Usage Performance Requirements and Installation FAQ Introduction Would
PyTorch implementation of HDN(Homography Decomposition Networks) for planar object tracking
Homography Decomposition Networks for Planar Object Tracking This project is the offical PyTorch implementation of HDN(Homography Decomposition Networ
Code for 2021 NeurIPS --- Towards Multi-Grained Explainability for Graph Neural Networks
ReFine: Multi-Grained Explainability for GNNs This is the official code for Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 20
Tensorflow Tutorials using Jupyter Notebook
Tensorflow Tutorials using Jupyter Notebook TensorFlow tutorials written in Python (of course) with Jupyter Notebook. Tried to explain as kindly as po
Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
LSTMs for Human Activity Recognition Human Activity Recognition (HAR) using smartphones dataset and an LSTM RNN. Classifying the type of movement amon
A deep learning network built with TensorFlow and Keras to classify gender and estimate age.
Convolutional Neural Network (CNN). This repository contains a source code of a deep learning network built with TensorFlow and Keras to classify gend
Deep Reinforcement Learning for Keras.
Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml
[CVPR 2020] Local Class-Specific and Global Image-Level Generative Adversarial Networks for Semantic-Guided Scene Generation
Contents Local and Global GAN Cross-View Image Translation Semantic Image Synthesis Acknowledgments Related Projects Citation Contributions Collaborat
O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis
O-CNN This repository contains the implementation of our papers related with O-CNN. The code is released under the MIT license. O-CNN: Octree-based Co
[ECCV'20] Convolutional Occupancy Networks
Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page | Blog Post This repository contains the implementation o
C3DPO - Canonical 3D Pose Networks for Non-rigid Structure From Motion.
C3DPO: Canonical 3D Pose Networks for Non-Rigid Structure From Motion By: David Novotny, Nikhila Ravi, Benjamin Graham, Natalia Neverova, Andrea Vedal
Volumetric Correspondence Networks for Optical Flow, NeurIPS 2019.
VCN: Volumetric correspondence networks for optical flow [project website] Requirements python 3.6 pytorch 1.1.0-1.3.0 pytorch correlation module (opt
Official Pytorch implementation of Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
Scene Representation Networks This is the official implementation of the NeurIPS submission "Scene Representation Networks: Continuous 3D-Structure-Aw
3D HourGlass Networks for Human Pose Estimation Through Videos
3D-HourGlass-Network 3D CNN Based Hourglass Network for Human Pose Estimation (3D Human Pose) from videos. This was my summer'18 research project. Dis
Build Low Code Automated Tensorflow, What-IF explainable models in just 3 lines of code.
Build Low Code Automated Tensorflow explainable models in just 3 lines of code.
Implementation of Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis
acLSTM_motion This folder contains an implementation of acRNN for the CMU motion database written in Pytorch. See the following links for more backgro
Something I built to test for Log4J vulnerabilities on customer networks.
Log4J-Scanner Something I built to test for Log4J vulnerabilities on customer networks. I'm not responsible if your computer blows up, catches fire or
Almost State-of-the-art Text Generation library
Ps: we are adding transformer model soon Text Gen 🐐 Almost State-of-the-art Text Generation library Text gen is a python library that allow you build
Codes for building and training the neural network model described in Domain-informed neural networks for interaction localization within astroparticle experiments.
Domain-informed Neural Networks Codes for building and training the neural network model described in Domain-informed neural networks for interaction
Pytorch implementation of our paper under review -- 1xN Pattern for Pruning Convolutional Neural Networks
1xN Pattern for Pruning Convolutional Neural Networks (paper) . This is Pytorch re-implementation of "1xN Pattern for Pruning Convolutional Neural Net
Implementation of Nalbach et al. 2017 paper.
Deep Shading Convolutional Neural Networks for Screen-Space Shading Our project is based on Nalbach et al. 2017 paper. In this project, a set of buffe
GANformer: Generative Adversarial Transformers
GANformer: Generative Adversarial Transformers Drew A. Hudson* & C. Lawrence Zitnick Update: We released the new GANformer2 paper! *I wish to thank Ch
This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels].
CGPN This is the repository for the NeurIPS-21 paper [Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels]. Req
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
Notice: Support for Python 3.6 will be dropped in v.0.2.1, please plan accordingly! Efficient and Scalable Physics-Informed Deep Learning Collocation-
PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
PyDEns PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks. With PyDEns one can solve PD
Physics-Informed Neural Networks (PINN) and Deep BSDE Solvers of Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
NeuralPDE NeuralPDE.jl is a solver package which consists of neural network solvers for partial differential equations using scientific machine learni
Sparse Physics-based and Interpretable Neural Networks
Sparse Physics-based and Interpretable Neural Networks for PDEs This repository contains the code and manuscript for research done on Sparse Physics-b
Implementation of Research Paper "Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation"
Zero-DCE and Zero-DCE++(Lite architechture for Mobile and edge Devices) Papers Abstract The paper presents a novel method, Zero-Reference Deep Curve E
Quickly visualize docker networks with graphviz.
Docker Network Graph Visualize the relationship between Docker networks and containers as a neat graphviz graph. Example Usage usage: docker-net-graph
This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm.
This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm. It contains the code to reproduce the results presented in the original paper: https://arxiv.org/abs/2112.03670
An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022
Dual Correlation Reduction Network An official source code for paper Deep Graph Clustering via Dual Correlation Reduction, accepted by AAAI 2022. Any
Hunt down social media accounts by username across social networks
Hunt down social media accounts by username across social networks Installation | Usage | Docker Notes | Contributing Installation # clone the repo $
Recursive Bayesian Networks
Recursive Bayesian Networks This repository contains the code to reproduce the results from the NeurIPS 2021 paper Lieck R, Rohrmeier M (2021) Recursi
[AAAI 2022] Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification
Sparse Structure Learning via Graph Neural Networks for inductive document classification Make graph dataset create co-occurrence graph for datasets.
Code for Contrastive-Geometry Networks for Generalized 3D Pose Transfer
CGTransformer Code for our AAAI 2022 paper "Contrastive-Geometry Transformer network for Generalized 3D Pose Transfer" Contrastive-Geometry Transforme
A high-performance distributed deep learning system targeting large-scale and automated distributed training.
HETU Documentation | Examples Hetu is a high-performance distributed deep learning system targeting trillions of parameters DL model training, develop
AI4Good project for detecting waste in the environment
Detect waste AI4Good project for detecting waste in environment. www.detectwaste.ml. Our latest results were published in Waste Management journal in
Generate high quality pictures. GAN. Generative Adversarial Networks
ESRGAN generate high quality pictures. GAN. Generative Adversarial Networks """ Super-resolution of CelebA using Generative Adversarial Networks. The
PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear
PyG (PyTorch Geometric) - A library built upon PyTorch to easily write and train Graph Neural Networks (GNNs)
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.
Official code for Next Check-ins Prediction via History and Friendship on Location-Based Social Networks (MDM 2018)
MUC Next Check-ins Prediction via History and Friendship on Location-Based Social Networks (MDM 2018) Performance Details for Accuracy: | Dataset
Official implementation of the article "Unsupervised JPEG Domain Adaptation For Practical Digital Forensics"
Unsupervised JPEG Domain Adaptation for Practical Digital Image Forensics @WIFS2021 (Montpellier, France) Rony Abecidan, Vincent Itier, Jeremie Boulan
Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks"
LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and
Code for Contrastive-Geometry Networks for Generalized 3D Pose Transfer
Code for Contrastive-Geometry Networks for Generalized 3D Pose Transfer
A PyTorch library and evaluation platform for end-to-end compression research
CompressAI CompressAI (compress-ay) is a PyTorch library and evaluation platform for end-to-end compression research. CompressAI currently provides: c
A library for researching neural networks compression and acceleration methods.
A library for researching neural networks compression and acceleration methods.
1st Solution For NeurIPS 2021 Competition on ML4CO Dual Task
KIDA: Knowledge Inheritance in Data Aggregation This project releases our 1st place solution on NeurIPS2021 ML4CO Dual Task. Slide and model weights a
A small library for doing fluid simulation with neural networks.
Neural Fluid Fields This is a small library for doing fluid simulation with neural fields. Check out our review paper, Neural Fields in Visual Computi
Official implementation of the paper "Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering"
Light Field Networks Project Page | Paper | Data | Pretrained Models Vincent Sitzmann*, Semon Rezchikov*, William Freeman, Joshua Tenenbaum, Frédo Dur
Plenoxels: Radiance Fields without Neural Networks
Plenoxels: Radiance Fields without Neural Networks Alex Yu*, Sara Fridovich-Keil*, Matthew Tancik, Qinhong Chen, Benjamin Recht, Angjoo Kanazawa UC Be
A modular PyTorch library for optical flow estimation using neural networks
A modular PyTorch library for optical flow estimation using neural networks
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"
Supplemental learning materials for "Fourier Feature Networks and Neural Volume Rendering"
Fourier Feature Networks and Neural Volume Rendering This repository is a companion to a lecture given at the University of Cambridge Engineering Depa
Plenoxels: Radiance Fields without Neural Networks, Code release WIP
Plenoxels: Radiance Fields without Neural Networks Alex Yu*, Sara Fridovich-Keil*, Matthew Tancik, Qinhong Chen, Benjamin Recht, Angjoo Kanazawa UC Be
[KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks
DiffMG This repository contains the code for our KDD 2021 Research Track paper: DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neura
A modular application for performing anomaly detection in networks
Deep-Learning-Models-for-Network-Annomaly-Detection The modular app consists for mainly three annomaly detection algorithms. The system supports model
Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks"
LUNAR Official Implementation of "LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks" Adam Goodge, Bryan Hooi, Ng See Kiong and
This repository is an implementation of paper : Improving the Training of Graph Neural Networks with Consistency Regularization
CRGNN Paper : Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090
Meandering In Networks of Entities to Reach Verisimilar Answers
MINERVA Meandering In Networks of Entities to Reach Verisimilar Answers Code and models for the paper Go for a Walk and Arrive at the Answer - Reasoni
Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks.
FDRL-PC-Dyspan Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks. This repository contains the entire code
The best solution of the Weather Prediction track in the Yandex Shifts challenge
yandex-shifts-weather The repository contains information about my solution for the Weather Prediction track in the Yandex Shifts challenge https://re
RID-Noise: Towards Robust Inverse Design under Noisy Environments
This is code of RID-Noise. Reproduce RID-Noise Results Toy tasks Please refer to the notebook ridnoise.ipynb to view experiments on three toy tasks. B
A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics, sequence features, and user profiles.
CCasGNN A new framework, collaborative cascade prediction based on graph neural networks (CCasGNN) to jointly utilize the structural characteristics,
Flexible Networks for Learning Physical Dynamics of Deformable Objects (2021)
Flexible Networks for Learning Physical Dynamics of Deformable Objects (2021) By Jinhyung Park, Dohae Lee, In-Kwon Lee from Yonsei University (Seoul,
SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolutional Networks
SalFBNet This repository includes Pytorch implementation for the following paper: SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolu
This repository is an implementation of paper : Improving the Training of Graph Neural Networks with Consistency Regularization
CRGNN Paper : Improving the Training of Graph Neural Networks with Consistency Regularization Environments Implementing environment: GeForce RTX™ 3090
Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks
Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks Work accepted at NeurIPS'21 [paper, video]. If you use this code in
An Implementation of Transformer in Transformer in TensorFlow for image classification, attention inside local patches
Transformer-in-Transformer An Implementation of the Transformer in Transformer paper by Han et al. for image classification, attention inside local pa
Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.
Federated learning on graph, especially on graph neural networks (GNNs), knowledge graph, and private GNN.
Papers about explainability of GNNs
Papers about explainability of GNNs
Pytorch code for "Text-Independent Speaker Verification Using 3D Convolutional Neural Networks".
:speaker: Deep Learning & 3D Convolutional Neural Networks for Speaker Verification
Unsupervised Image to Image Translation with Generative Adversarial Networks
Unsupervised Image to Image Translation with Generative Adversarial Networks Paper: Unsupervised Image to Image Translation with Generative Adversaria
The implementation code for "DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction"
DAGAN This is the official implementation code for DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruct
Dynamic Capacity Networks using Tensorflow
Dynamic Capacity Networks using Tensorflow Dynamic Capacity Networks (DCN; http://arxiv.org/abs/1511.07838) implementation using Tensorflow. DCN reduc
TensorFlow implementation of the paper "Hierarchical Attention Networks for Document Classification"
Hierarchical Attention Networks for Document Classification This is an implementation of the paper Hierarchical Attention Networks for Document Classi
End-To-End Memory Network using Tensorflow
MemN2N Implementation of End-To-End Memory Networks with sklearn-like interface using Tensorflow. Tasks are from the bAbl dataset. Get Started git clo
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In
CNN visualization tool in TensorFlow
tf_cnnvis A blog post describing the library: https://medium.com/@falaktheoptimist/want-to-look-inside-your-cnn-we-have-just-the-right-tool-for-you-ad
Deep Learning & 3D Convolutional Neural Networks for Speaker Verification
TensorFlow implementation of 3D Convolutional Neural Networks for Speaker Verification - Official Project Page - Pytorch Implementation This repositor
Lip Reading - Cross Audio-Visual Recognition using 3D Convolutional Neural Networks
Lip Reading - Cross Audio-Visual Recognition using 3D Convolutional Neural Networks - Official Project Page This repository contains the code develope
A Tensorfflow implementation of Attend, Infer, Repeat
Attend, Infer, Repeat: Fast Scene Understanding with Generative Models This is an unofficial Tensorflow implementation of Attend, Infear, Repeat (AIR)
Semi-Supervised Learning with Ladder Networks in Keras. Get 98% test accuracy on MNIST with just 100 labeled examples !
Semi-Supervised Learning with Ladder Networks in Keras This is an implementation of Ladder Network in Keras. Ladder network is a model for semi-superv
Run Keras models in the browser, with GPU support using WebGL
**This project is no longer active. Please check out TensorFlow.js.** The Keras.js demos still work but is no longer updated. Run Keras models in the
Training Structured Neural Networks Through Manifold Identification and Variance Reduction
Training Structured Neural Networks Through Manifold Identification and Variance Reduction This repository is a pytorch implementation of the Regulari
Learning Tracking Representations via Dual-Branch Fully Transformer Networks
Learning Tracking Representations via Dual-Branch Fully Transformer Networks DualTFR ⭐ We achieves the runner-ups for both VOT2021ST (short-term) and
Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification (NeurIPS 2021)
Graph Posterior Network This is the official code repository to the paper Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classifica
Alternatives to Deep Neural Networks for Function Approximations in Finance
Alternatives to Deep Neural Networks for Function Approximations in Finance Code companion repo Overview This is a repository of Python code to go wit
Convert ONNX model graph to Keras model format.
Convert ONNX model graph to Keras model format.
Object Detection with YOLOv3
Object Detection with YOLOv3 Bu projede YOLOv3-608 modeli kullanılmıştır. Requirements Python 3.8 OpenCV Numpy Documentation Yolo ile ilgili detaylı b
Source code and dataset of the paper "Contrastive Adaptive Propagation Graph Neural Networks forEfficient Graph Learning"
CAPGNN Source code and dataset of the paper "Contrastive Adaptive Propagation Graph Neural Networks forEfficient Graph Learning" Paper URL: https://ar
TC-GNN with Pytorch integration
TC-GNN (Running Sparse GNN on Dense Tensor Core on Ampere GPU) Cite this project and paper. @inproceedings{TC-GNN, title={TC-GNN: Accelerating Spars
Efficient Two-Step Networks for Temporal Action Segmentation (Neurocomputing 2021)
Efficient Two-Step Networks for Temporal Action Segmentation This repository provides a PyTorch implementation of the paper Efficient Two-Step Network
An assignment from my grad-level data mining course demonstrating some experience with NLP/neural networks/Pytorch
NLP-Pytorch-Assignment An assignment from my grad-level data mining course (before I started personal projects) demonstrating some experience with NLP
With Py-Autocrack you can crack WPA2 networks in no time.
With Py-Autocrack you can crack WPA2 networks in no time. All based on Aircrack-ng and Crunch.
Noise Conditional Score Networks (NeurIPS 2019, Oral)
Generative Modeling by Estimating Gradients of the Data Distribution This repo contains the official implementation for the NeurIPS 2019 paper Generat
A Loss Function for Generative Neural Networks Based on Watson’s Perceptual Model
This repository contains the similarity metrics designed and evaluated in the paper, and instructions and code to re-run the experiments. Implementation in the deep-learning framework PyTorch