2053 Repositories
Python Neural-Koopman-Lyapunov-Control Libraries
Autoencoder - Reducing the Dimensionality of Data with Neural Network
autoencoder Implementation of the Reducing the Dimensionality of Data with Neural Network – G. E. Hinton and R. R. Salakhutdinov paper. Notes Aim to m
Convnet transfer - Code for paper How transferable are features in deep neural networks?
How transferable are features in deep neural networks? This repository contains source code necessary to reproduce the results presented in the follow
Deep-Learning-Image-Captioning - Implementing convolutional and recurrent neural networks in Keras to generate sentence descriptions of images
Deep Learning - Image Captioning with Convolutional and Recurrent Neural Nets ========================================================================
Image captioning - Tensorflow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
Introduction This neural system for image captioning is roughly based on the paper "Show, Attend and Tell: Neural Image Caption Generation with Visual
Nmt - TensorFlow Neural Machine Translation Tutorial
Neural Machine Translation (seq2seq) Tutorial Authors: Thang Luong, Eugene Brevdo, Rui Zhao (Google Research Blogpost, Github) This version of the tut
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)
Projeto-menu - This project is designed to learn more about control mechanisms in Python programming
Projeto-menu - This project is designed to learn more about control mechanisms in Python programming
Control-Raspberry-Pi-Robot-using-Hand-Gestures - A 4WD Robot car based on Raspberry Pi that controlled by hand gestures(using openCV and mediapipe)
Control-Raspberry-Pi-Robot-using-Hand-Gestures you can see all details about thi
Distributed Grid Descent: an algorithm for hyperparameter tuning guided by Bayesian inference, designed to run on multiple processes and potentially many machines with no central point of control
Distributed Grid Descent: an algorithm for hyperparameter tuning guided by Bayesian inference, designed to run on multiple processes and potentially many machines with no central point of control.
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.
🕵 Artificial Intelligence for social control of public administration
Non-tech crash course into Operação Serenata de Amor Tech crash course into Operação Serenata de Amor Contributing with code and tech skills Supportin
Augmented Traffic Control: A tool to simulate network conditions
Augmented Traffic Control Full documentation for the project is available at http://facebook.github.io/augmented-traffic-control/. Overview Augmented
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
Skiller - With this payload you can control the target computer with (cmd)
Skiller - With this payload you can control the target computer with (cmd)
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
Control-Robot-Arm-using-PS4-Controller - A Robotic Arm based on Raspberry Pi and Arduino that controlled by PS4 Controller
Control-Robot-Arm-using-PS4-Controller You can see all details about this Robot
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:/
Gesture-Volume-Control - This Python program can adjust the system's volume by using hand gestures
Gesture-Volume-Control This Python program can adjust the system's volume by usi
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
Vibrating-perimeter - Simple helper mod that logs how fast you are mining together with a simple buttplug.io script to control a vibrator
Vibrating Perimeter This project consists of a small minecraft helper mod that writes too a log file and a script that reads said log. Currently it on
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 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
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
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.
inverted pendulum fuzzy control python code (python 2.7.18)
inverted-pendulum-fuzzy-control- inverted pendulum fuzzy control python code (python 2.7.18) We have 3 general functions for 3 main steps: fuzzificati
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
Pypot ⚙️ A Python library for Dynamixel motor control
Pypot ⚙️ A Python library for Dynamixel motor control Pypot is a cross-platform Python library making it easy and fast to control custom robots based
Control the lights of Alienware computers under GNU/Linux systems.
Before requesting support please consider that this software is not actively developed. I created it in 2014 for managing my Alienware M14X-R1 (where
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
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,
The implementation of Parameter Differentiation based Multilingual Neural Machine Translation
The implementation of Parameter Differentiation based Multilingual Neural Machin
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,
Mycodo is open source software for the Raspberry Pi that couples inputs and outputs in interesting ways to sense and manipulate the environment.
Mycodo Environmental Regulation System Latest version: 8.12.9 Mycodo is open source software for the Raspberry Pi that couples inputs and outputs in i
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
A simple python project which control paint brush in microsoft paint app
Paint Buddy In Python A simple python project which control paint brush in micro
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
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size.
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size. The hub data layout enables rapid transformations and streaming of data while training models at scale. Hub is used by Google, Waymo, Red Cross, Oxford University, and Omdena.
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
Detection And Breaking With Python
Detection And Breaking IIIIIIIIIIIIIIIIIIII PPPPPPPPPPPPPPPPP VVVVVVVV VVVVVVVV I::::::::II::::::::I P:::::::
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
Neptune client library - integrate your Python scripts with Neptune
Lightweight experiment tracking tool for AI/ML individuals and teams. Fits any workflow. Neptune is a lightweight experiment logging/tracking tool tha
An open-source systems and controls toolbox for Python3
harold A control systems package for Python=3.6. Introduction This package is written with the ambition of providing a full-fledged control systems s
Render template parts with extended cache control.
Render template parts with extended cache control. Installation Install django-viewlet in your python environment $ pip install django-viewlet Support
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