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Code for Improving Deep Neural Network with Multiple Parametric Exponential Linear Units
[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
Official implementation of Cold-Diffusion for different transformations in pytorch.
Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training
Examples of training models with hybrid parallelism using ColossalAI
Official implementation of CVPR2020 paper: "Compositional Convolutional Neural Networks: A Deep Architecture with Innate Robustness to Partial Occlusion" https://arxiv.org/abs/2003.04490
PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, DGR, DGR+distill, RtF, iCaRL).
Spatio-temporal video autoencoder with convolutional LSTMs
Memory consumption and FLOP count estimates for convnets
Text Classification ToolKit
Documentation for the OpenHW Group's set of CORE-V RISC-V cores
Functional verification project for the CORE-V family of RISC-V cores.
Ethernet MAC 10/100 Mbps
Stanford CoreNLP: A Java suite of core NLP tools.
Various HDL (Verilog) IP Cores
Matlab GPU Accelerated Deep Learning Toolbox
We are building an open database of COVID-19 cases with chest X-ray or CT images.
COVID-CT-Dataset: A CT Scan Dataset about COVID-19
Train CPPNs as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.
Very Simple and Basic Implementation of Compositional Pattern Producing Network in TensorFlow
Custom fork of CppUTest unit testing code that I use from multiple projects.
Catch Hard Faults on Cortex-M devices and save out a crash dump to be used by CrashDebug.
Tool to enable post-mortem debugging of Cortex-M crashes with GDB.
Character-level Convolutional Networks for Text Classification
A database system that can process SQL queries over encrypted data.
golang std package crypto implementate sm2, sm3, sm4
After watching all the videos of the famous Standford's CS231n course that took place in 2017, i decided to take summary of the whole course to help me to remember and to anyone who would like to know about it. I've skipped some contents in some lectures as it wasn't important to me.
Public facing notes page
Automatically exported from code.google.com/p/cuda-convnet
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.