2074 Repositories
Python Neural-Scene-Flow-Fields Libraries
Computer-Vision-Paper-Reviews - Computer Vision Paper Reviews with Key Summary along Papers & Codes
Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 50+ Papers across Computer Visio
SimpleDepthEstimation - An unified codebase for NN-based monocular depth estimation methods
SimpleDepthEstimation Introduction This is an unified codebase for NN-based monocular depth estimation methods, the framework is based on detectron2 (
A video scene detection algorithm is designed to detect a variety of different scenes within a video
Scene-Change-Detection - A video scene detection algorithm is designed to detect a variety of different scenes within a video. There is a very simple definition for a scene: It is a series of logically and chronologically related shots taken in a specific order to depict an over-arching concept or story.
LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating
LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating (Dataset) The dataset is from Amazon Review Data (2018)
BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work
BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work. For this project, I used the sigmoid function as an activation function along with stochastic gradient descent to adjust the weights and biases.
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.
AutoGluon: AutoML for Text, Image, and Tabular Data
AutoML for Text, Image, and Tabular Data AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in yo
Imagededup - 😎 Finding duplicate images made easy
imagededup is a python package that simplifies the task of finding exact and near duplicates in an image collection.
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano
Please read the blog post that goes with this code! Jupyter Notebook Setup System Requirements: Python, pip (Optional) virtualenv To start the Jupyter
Gans-in-action - Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
GANs in Action by Jakub Langr and Vladimir Bok List of available code: Chapter 2: Colab, Notebook Chapter 3: Notebook Chapter 4: Notebook Chapter 6: C
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai
Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
PyTorch-Multi-Style-Transfer - Neural Style and MSG-Net
PyTorch-Style-Transfer This repo provides PyTorch Implementation of MSG-Net (ours) and Neural Style (Gatys et al. CVPR 2016), which has been included
Speech-Emotion-Analyzer - The neural network model is capable of detecting five different male/female emotions from audio speeches. (Deep Learning, NLP, Python)
Speech Emotion Analyzer The idea behind creating this project was to build a machine learning model that could detect emotions from the speech we have
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models
Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor
Nerf pl - NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning
nerf_pl Update: an improved NSFF implementation to handle dynamic scene is open! Update: NeRF-W (NeRF in the Wild) implementation is added to nerfw br
TensorFlow 101: Introduction to Deep Learning for Python Within TensorFlow
TensorFlow 101: Introduction to Deep Learning I have worked all my life in Machine Learning, and I've never seen one algorithm knock over its benchmar
Saliency - Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).
Saliency Methods 🔴 Now framework-agnostic! (Example core notebook) 🔴 🔗 For further explanation of the methods and more examples of the resulting ma
Detectron2-FC a fast construction platform of neural network algorithm based on detectron2
What is Detectron2-FC Detectron2-FC a fast construction platform of neural network algorithm based on detectron2. We have been working hard in two dir
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Created by Charles R. Qi, Hao Su, Kaichun Mo, Leonidas J. Guibas from Sta
Generate image analogies using neural matching and blending
neural image analogies This is basically an implementation of this "Image Analogies" paper, In our case, we use feature maps from VGG16. The patch mat
Tensorflow-Project-Template - A best practice for tensorflow project template architecture.
Tensorflow Project Template A simple and well designed structure is essential for any Deep Learning project, so after a lot of practice and contributi
Public repository containing materials used for Feed Forward (FF) Neural Networks article.
Art041_NN_Feed_Forward Public repository containing materials used for Feed Forward (FF) Neural Networks article. -- Illustration of a very simple Fee
Simple-Neural-Network From Scratch in Python
Simple-Neural-Network From Scratch in Python This is a simple Neural Network created without any Machine Learning Libraries. The only dependencies are
Losslandscapetaxonomy - Taxonomizing local versus global structure in neural network loss landscapes
Taxonomizing local versus global structure in neural network loss landscapes Int
Cancer-and-Tumor-Detection-Using-Inception-model - In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks, specifically here the Inception model by google.
Cancer-and-Tumor-Detection-Using-Inception-model In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks
BRNet - code for Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss function
BRNet code for "Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss func
CS5242_2021 - Neural Networks and Deep Learning, NUS CS5242, 2021
CS5242_2021 Neural Networks and Deep Learning, NUS CS5242, 2021 Cloud Machine #1 : Google Colab (Free GPU) Follow this Notebook installation : https:/
Siamese-nn-semantic-text-similarity - A repository containing comprehensive Neural Networks based PyTorch implementations for the semantic text similarity task
Siamese Deep Neural Networks for Semantic Text Similarity PyTorch A repository c
Ppq - A powerful offline neural network quantization tool with custimized IR
PPL Quantization Tool(PPL 量化工具) PPL Quantization Tool (PPQ) is a powerful offlin
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto
Self Governing Neural Networks (SGNN): the Projection Layer
Self Governing Neural Networks (SGNN): the Projection Layer A SGNN's word projections preprocessing pipeline in scikit-learn In this notebook, we'll u
Neural-fractal - Create Fractals Using Complex-Valued Neural Networks!
Neural Fractal Create Fractals Using Complex-Valued Neural Networks! Home Page Features Define Dynamical Systems Using Complex-Valued Neural Networks
SOTA easy to use PyTorch-based DL training library
Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open
The official MegEngine implementation of the ICCV 2021 paper: GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning
[ICCV 2021] GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning This is the official implementation of our ICCV2021 paper GyroFlow. Our pres
The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.
Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode
Weakly- and Semi-Supervised Panoptic Segmentation (ECCV18)
Weakly- and Semi-Supervised Panoptic Segmentation by Qizhu Li*, Anurag Arnab*, Philip H.S. Torr This repository demonstrates the weakly supervised gro
PyTorch implementation of Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose
Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Release Notes The official PyTorch implementation of Neural View S
Implementation of ICLR 2020 paper "Revisiting Self-Training for Neural Sequence Generation"
Self-Training for Neural Sequence Generation This repo includes instructions for running noisy self-training algorithms from the following paper: Revi
Neural network sequence labeling model
Sequence labeler This is a neural network sequence labeling system. Given a sequence of tokens, it will learn to assign labels to each token. Can be u
PyTorch implementation of the Flow Gaussian Mixture Model (FlowGMM) model from our paper
Flow Gaussian Mixture Model (FlowGMM) This repository contains a PyTorch implementation of the Flow Gaussian Mixture Model (FlowGMM) model from our pa
Training neural models with structured signals.
Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured
SemiNAS: Semi-Supervised Neural Architecture Search
SemiNAS: Semi-Supervised Neural Architecture Search This repository contains the code used for Semi-Supervised Neural Architecture Search, by Renqian
PyTorch implementation for Graph Contrastive Learning with Augmentations
Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*
Decensoring Hentai with Deep Neural Networks. Formerly named DeepMindBreak.
DeepCreamPy Decensoring Hentai with Deep Neural Networks. Formerly named DeepMindBreak. A deep learning-based tool to automatically replace censored a
A simplistic and efficient pure-python neural network library from Phys Whiz with CPU and GPU support.
A simplistic and efficient pure-python neural network library from Phys Whiz with CPU and GPU support.
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N
A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"
SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th
Pretraining on Dynamic Graph Neural Networks
Pretraining on Dynamic Graph Neural Networks Our article is PT-DGNN and the code is modified based on GPT-GNN Requirements python 3.6 Ubuntu 18.04.5 L
An implementation of Deep Graph Infomax (DGI) in PyTorch
DGI Deep Graph Infomax (Veličković et al., ICLR 2019): https://arxiv.org/abs/1809.10341 Overview Here we provide an implementation of Deep Graph Infom
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning
Graph-InfoClust-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu
ncnn is a high-performance neural network inference framework optimized for the mobile platform
ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme
Minimal implementation and experiments of "No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging".
No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging Minimal implementation and experiments of "No-Transaction Band N
Numerical Methods with Python, Numpy and Matplotlib
Numerical Bric-a-Brac Collections of numerical techniques with Python and standard computational packages (Numpy, SciPy, Numba, Matplotlib ...). Diffe
Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs.
Lunar Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs. About Lunar can be modified to work
Code repository accompanying the paper "On Adversarial Robustness: A Neural Architecture Search perspective"
On Adversarial Robustness: A Neural Architecture Search perspective Preparation: Clone the repository: https://github.com/tdchaitanya/nas-robustness.g
A NASA MEaSUREs project to provide automated, low latency, global glacier flow and elevation change datasets
Notebooks A NASA MEaSUREs project to provide automated, low latency, global glacier flow and elevation change datasets This repository provides tools
General neural ODE and DAE modules for power system dynamic modeling.
Py_PSNODE General neural ODE and DAE modules for power system dynamic modeling. The PyTorch-based ODE solver is developed based on torchdiffeq. Sample
The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
Block Modeling-Guided Graph Convolutional Neural Networks This repository contains the demo code of the paper: Block Modeling-Guided Graph Convolution
The implementation of Parameter Differentiation based Multilingual Neural Machine Translation .
The implementation of Parameter Differentiation based Multilingual Neural Machine Translation .
Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm
Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism"
SUGAR Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism" Overview train.py: the cor
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
NeoDTI NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions (Bioinformatics).
Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"
SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation.
Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training
PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be
Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa
code for "Self-supervised edge features for improved Graph Neural Network training", arxivlink
Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.
[ICML 2020] DrRepair: Learning to Repair Programs from Error Messages
DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program
Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.
Official PyTorch implementation of the paper: "Self-Supervised Relational Reasoning for Representation Learning" (2020), Patacchiola, M., and Storkey,
Code for the paper: Audio-Visual Scene Analysis with Self-Supervised Multisensory Features
[Paper] [Project page] This repository contains code for the paper: Andrew Owens, Alexei A. Efros. Audio-Visual Scene Analysis with Self-Supervised Mu
The implementation of Parameter Differentiation based Multilingual Neural Machine Translation
The implementation of Parameter Differentiation based Multilingual Neural Machin
Scene-Text-Detection-and-Recognition (Pytorch)
Scene-Text-Detection-and-Recognition (Pytorch) Competition URL: https://tbrain.t
Finite-temperature variational Monte Carlo calculation of uniform electron gas using neural canonical transformation.
CoulombGas This code implements the neural canonical transformation approach to the thermodynamic properties of uniform electron gas. Building on JAX,
A short term landscape evolution using a path sampling method to solve water and sediment flow continuity equations and model mass flows over complex topographies.
r.sim.terrain A short-term landscape evolution model that simulates topographic change for both steady state and dynamic flow regimes across a range o
Fast, DB Backed pretrained word embeddings for natural language processing.
Embeddings Embeddings is a python package that provides pretrained word embeddings for natural language processing and machine learning. Instead of lo
PyTorch Implementation for Deep Metric Learning Pipelines
Easily Extendable Basic Deep Metric Learning Pipeline Karsten Roth ([email protected]), Biagio Brattoli ([email protected]) When using thi
Implementation of Memory-Efficient Neural Networks with Multi-Level Generation, ICCV 2021
Memory-Efficient Multi-Level In-Situ Generation (MLG) By Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen and David Z. Pan
Characterizing possible failure modes in physics-informed neural networks.
Characterizing possible failure modes in physics-informed neural networks This repository contains the PyTorch source code for the experiments in the
Traditional deepdream with VQGAN+CLIP and optical flow. Ready to use in Google Colab
VQGAN-CLIP-Video cat.mp4 policeman.mp4 schoolboy.mp4 forsenBOG.mp4
An add to make adding screenshots and copied images to the scene easy
Blender Clipboard to Scene It doesn't work with version 2.93 and higher (I tested it on 2.91 and 2.83) There is an issue with importing the Pillow mod
RCDNet: A Model-driven Deep Neural Network for Single Image Rain Removal (CVPR2020)
RCDNet: A Model-driven Deep Neural Network for Single Image Rain Removal (CVPR2020) Hong Wang, Qi Xie, Qian Zhao, and Deyu Meng [PDF] [Supplementary M
Code to use Augmented Shapiro Wilks Stopping, as well as code for the paper "Statistically Signifigant Stopping of Neural Network Training"
This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea
Neural network chess engine trained on Gary Kasparov's games.
Neural Chess It's not the best chess engine, but it is a chess engine. Proof of concept neural network chess engine (feed-forward multi-layer perceptr
[PNAS2021] The neural architecture of language: Integrative modeling converges on predictive processing
The neural architecture of language: Integrative modeling converges on predictive processing Code accompanying the paper The neural architecture of la
Source code of SIGIR2021 Paper 'One Chatbot Per Person: Creating Personalized Chatbots based on Implicit Profiles'
DHAP Source code of SIGIR2021 Long Paper: One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles . Preinstallation Fir
Official PyTorch Implementation of paper "NeLF: Neural Light-transport Field for Single Portrait View Synthesis and Relighting", EGSR 2021.
NeLF: Neural Light-transport Field for Single Portrait View Synthesis and Relighting Official PyTorch Implementation of paper "NeLF: Neural Light-tran
A visualization tool to show a TensorFlow's graph like TensorBoard
tfgraphviz tfgraphviz is a module to visualize a TensorFlow's data flow graph like TensorBoard using Graphviz. tfgraphviz enables to provide a visuali
An End-to-End Machine Learning Library to Optimize AUC (AUROC, AUPRC).
Logo by Zhuoning Yuan LibAUC: A Machine Learning Library for AUC Optimization Website | Updates | Installation | Tutorial | Research | Github LibAUC a
ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python)
ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python) 日本語は以下に続きます (Japanese follows) English: This book is written in Japanese and primaril
A websocket client for Source Filmmaker intended to trasmit scene and frame data to other applications.
SFM SOCK A websocket client for Source Filmmaker intended to trasmit scene and frame data to other applications. This software can be used to transmit
Python package for the analysis and visualisation of finite-difference fields.
discretisedfield Marijan Beg1,2, Martin Lang2, Samuel Holt3, Ryan A. Pepper4, Hans Fangohr2,5,6 1 Department of Earth Science and Engineering, Imperia
Super Resolution for images using deep learning.
Neural Enhance Example #1 — Old Station: view comparison in 24-bit HD, original photo CC-BY-SA @siv-athens. As seen on TV! What if you could increase
A minimal TPU compatible Jax implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
NeRF Minimal Jax implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. Result of Tiny-NeRF RGB Depth
Official PyTorch implementation of "Evolving Search Space for Neural Architecture Search"
Evolving Search Space for Neural Architecture Search Usage Install all required dependencies in requirements.txt and replace all ..path/..to in the co
Official PyTorch Implementation of paper "NeLF: Neural Light-transport Field for Single Portrait View Synthesis and Relighting", EGSR 2021.
NeLF: Neural Light-transport Field for Single Portrait View Synthesis and Relighting Official PyTorch Implementation of paper "NeLF: Neural Light-tran
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search
Breaking the Curse of Space Explosion: Towards Effcient NAS with Curriculum Search Pytorch implementation for "Breaking the Curse of Space Explosion:
Code for MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks
MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks This is the code for the paper: MentorNet: Learning Data-Driven Curriculum fo
Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes, ICCV 2017
AdaptationSeg This is the Python reference implementation of AdaptionSeg proposed in "Curriculum Domain Adaptation for Semantic Segmentation of Urban