Glcic PytorchA High-Quality PyTorch Implementation of "Globally and Locally Consistent Image Completion".
Stars: ✭ 141 (-14.55%)
Go Perceptron GoA single / multi layer / recurrent neural network written in Golang.
Stars: ✭ 159 (-3.64%)
BenderEasily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.
Stars: ✭ 1,728 (+947.27%)
MagiclMatrix Algebra proGrams In Common Lisp.
Stars: ✭ 140 (-15.15%)
MobulaopA Simple & Flexible Cross Framework Operators Toolkit
Stars: ✭ 161 (-2.42%)
NptdmsNumPy based Python module for reading TDMS files produced by LabView
Stars: ✭ 138 (-16.36%)
CryptonetsCryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.
Stars: ✭ 152 (-7.88%)
Brain BitsA P300 online spelling mechanism for Emotiv headsets. It's completely written in Node.js, and the GUI is based on Electron and Vue.
Stars: ✭ 138 (-16.36%)
Deep CfrScalable Implementation of Deep CFR and Single Deep CFR
Stars: ✭ 158 (-4.24%)
BnafPytorch implementation of Block Neural Autoregressive Flow
Stars: ✭ 138 (-16.36%)
IresnetImproved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)
Stars: ✭ 163 (-1.21%)
FlowppCode for reproducing Flow ++ experiments
Stars: ✭ 137 (-16.97%)
LabsLabs for the Foundations of Applied Mathematics curriculum.
Stars: ✭ 150 (-9.09%)
Ml CheatsheetA constantly updated python machine learning cheatsheet
Stars: ✭ 136 (-17.58%)
Capsule Net Pytorch[NO MAINTENANCE INTENDED] A PyTorch implementation of CapsNet architecture in the NIPS 2017 paper "Dynamic Routing Between Capsules".
Stars: ✭ 158 (-4.24%)
Pytorch 101 Tutorial SeriesPyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.
Stars: ✭ 136 (-17.58%)
Ai BlocksA powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!
Stars: ✭ 1,818 (+1001.82%)
Deep Learning With PythonExample projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.
Stars: ✭ 134 (-18.79%)
DnwDiscovering Neural Wirings (https://arxiv.org/abs/1906.00586)
Stars: ✭ 133 (-19.39%)
FrvsrFrame-Recurrent Video Super-Resolution (official repository)
Stars: ✭ 157 (-4.85%)
Stb TesterAutomated Testing for Set-Top Boxes and Smart TVs
Stars: ✭ 148 (-10.3%)
JyniEnables Jython to load native CPython extensions.
Stars: ✭ 131 (-20.61%)
TaTechnical Analysis Library using Pandas and Numpy
Stars: ✭ 2,649 (+1505.45%)
WyrmAutodifferentiation package in Rust.
Stars: ✭ 164 (-0.61%)
Numscanumsca is numpy for scala
Stars: ✭ 160 (-3.03%)
Cam boardTurn web cam into a black / white board
Stars: ✭ 157 (-4.85%)
Stock Price PredictorThis project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
Stars: ✭ 146 (-11.52%)
Pyjson tricksExtra features for Python's JSON: comments, order, numpy, pandas, datetimes, and many more! Simple but customizable.
Stars: ✭ 131 (-20.61%)
RobinRObust document image BINarization
Stars: ✭ 131 (-20.61%)
Textfeatures👷♂️ A simple package for extracting useful features from character objects 👷♀️
Stars: ✭ 148 (-10.3%)
Root numpyThe interface between ROOT and NumPy
Stars: ✭ 130 (-21.21%)
OrjsonFast, correct Python JSON library supporting dataclasses, datetimes, and numpy
Stars: ✭ 2,595 (+1472.73%)
PersephoneA tool for automatic phoneme transcription
Stars: ✭ 130 (-21.21%)
ForpyForpy - use Python from Fortran
Stars: ✭ 129 (-21.82%)
Msgpack NumpySerialize numpy arrays using msgpack
Stars: ✭ 147 (-10.91%)
Tiny mlnumpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法
Stars: ✭ 129 (-21.82%)
PysnnEfficient Spiking Neural Network framework, built on top of PyTorch for GPU acceleration
Stars: ✭ 129 (-21.82%)
GatGraph Attention Networks (https://arxiv.org/abs/1710.10903)
Stars: ✭ 2,229 (+1250.91%)
Math PhpPowerful modern math library for PHP: Features descriptive statistics and regressions; Continuous and discrete probability distributions; Linear algebra with matrices and vectors, Numerical analysis; special mathematical functions; Algebra
Stars: ✭ 2,009 (+1117.58%)
RocblasNext generation BLAS implementation for ROCm platform
Stars: ✭ 147 (-10.91%)
Scarpet NnTools and libraries to run neural networks in Minecraft ⛏
Stars: ✭ 129 (-21.82%)
NumcppC++ implementation of the Python Numpy library
Stars: ✭ 2,031 (+1130.91%)
Merlin.jlDeep Learning for Julia
Stars: ✭ 147 (-10.91%)
JevoisJeVois smart machine vision framework
Stars: ✭ 128 (-22.42%)
NettackImplementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".
Stars: ✭ 156 (-5.45%)
Autograd.jlJulia port of the Python autograd package.
Stars: ✭ 147 (-10.91%)
BanditmlA lightweight contextual bandit & reinforcement learning library designed to be used in production Python services.
Stars: ✭ 127 (-23.03%)
JsnetJavascript/WebAssembly deep learning library for MLPs and convolutional neural networks
Stars: ✭ 126 (-23.64%)