Search Results for "neural net"
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Showing 31 open source projects for "neural net"
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MIVisionX
Set of comprehensive computer vision & machine intelligence libraries
MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning inference... -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN... -
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PySR
High-Performance Symbolic Regression in Python and Julia
... are described in the PySR paper. Symbolic regression works best on low-dimensional datasets, but one can also extend these approaches to higher-dimensional spaces by using "Symbolic Distillation" of Neural Networks, as explained in 2006.11287, where we apply it to N-body problems. Here, one essentially uses symbolic regression to convert a neural net to an analytic equation. Thus, these tools simultaneously present an explicit and powerful way to interpret deep neural networks. -
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DeepCTR-Torch
Easy-to-use,Modular and Extendible package of deep-learning models
... features and some dense numerical features. Low-order Extractor learns feature interaction through product between vectors. Factorization-Machine and it’s variants are widely used to learn the low-order feature interaction. High-order Extractor learns feature combination through complex neural network functions like MLP, Cross Net, etc. -
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LLaMA.go
llama.go is like llama.cpp in pure Golang
llama.go is like llama.cpp in pure Golang. The code of the project is based on the legendary ggml.cpp framework of Georgi Gerganov written in C++ with the same attitude to performance and elegance. Both models store FP32 weights, so you'll needs at least 32Gb of RAM (not VRAM or GPU RAM) for LLaMA-7B. Double to 64Gb for LLaMA-13B. -
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BlackBelt WASTE - ipv4/Tor/i2p +AI+Voice
Modern, AI-Smart, WASTE p2p for ipv4, Tor and i2p + Voice Conference.
...-Performance-Tuning - A Goal-Seeking Swarming-Semiotic AI *** AI Connect - AI Managed Connections. *** Self-Organising Anti-Spoofing Technology *** Geared Multi-threading, providing the smoothest performance possible *** Advanced Threat Detect and Manage Technology *** Voice Conferencing Over WASTE *** RNN - Recurring Neural Net - AI Noise Reduction -
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NiftyNet
An open-source convolutional neural networks platform for research
An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging... -
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Tensorpack
A Neural Net Training Interface on TensorFlow, with focus on speed
Tensorpack is a neural network training interface based on TensorFlow v1. Uses TensorFlow in the efficient way with no extra overhead. On common CNNs, it runs training 1.2~5x faster than the equivalent Keras code. Your training can probably gets faster if written with Tensorpack. Scalable data-parallel multi-GPU / distributed training strategy is off-the-shelf to use. Squeeze the best data loading performance of Python with tensorpack.dataflow. Symbolic programming (e.g. tf.data) does not offer... -
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DaNNet
Deep Artificial Neural Network framework using Armadillo
DaNNet is a C++ deep neural network library using the Armadillo library as a base. It is intended to be a small and easy to use framework with no other dependencies than Armadillo. It uses independent layer-wise optimization giving you full flexibility to train your network. -
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OpenDino
Open Source Java platform for Optimization, DoE, and Learning.
OpenDino is an open source Java platform for optimization, design of experiment and learning. It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules". Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing other programs (solvers... -
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Neural Network signal recognition rtlsdr
Deep learning signal classification (recognition) using rtl-sdr dongle
WARNING: Outdated version here. Everything has been moved to github: https://github.com/randaller/cnn-rtlsdr -
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mAP
Evaluates the performance of your neural net for object recognition
In practice, a higher mAP value indicates a better performance of your neural net, given your ground truth and set of classes. The performance of your neural net will be judged using the mAP criteria defined in the PASCAL VOC 2012 competition. We simply adapted the official Matlab code into Python (in our tests they both give the same results). First, your neural net detection-results are sorted by decreasing confidence and are assigned to ground-truth objects. We have "a match" when they share... -
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Autograd
Efficiently computes derivatives of numpy code
Autograd can automatically differentiate native Python and Numpy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily.... -
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MetaNet
Free portable library for meta neural network research
MetaNet provides free library for meta neural network research. MetaNet library contain feed-forward neural net realisation and several integrated dataset (MNIST). -
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Java class libraries for structural biology development: includes protein format conversion tool, printf-based text formatting, Pred2ary secondary structure prediction, neural net library, Hooke-Jeeves global optimizer, and misc. math & statistics.
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DropoutMLP
A Multi-Layer Perceptron with Dropout
This project was derived from the following project on CCodeChamp by MR CODER. http://www.ccodechamp.com/c-program-of-multilayer-perceptron-net-using-backpropagation/ I rewrote the project in C++ and and made it more object oriented. Then, I added the capability to use dropout on the hidden layers as specified by Geoffrey Hinton et. al. in "Improving neural networks by preventing co-adaptation of feature detectors" (2012). http://www.cs.toronto.edu/~hinton/absps/dropout.pdf I found... -
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TronTool
Tuning of java neuroph.org neural nets.
By using a neural net from neuroph.org with the programmlanguage Java, you can change the net by this software. Easy watch it on the screen and move the values up or down. More or less value at the output neurons. Saving, Loading from different .nnet`s. Adding comments. Changing the visible output neuron Setting wished input neurons to get visible. A small fast and easy weight version and a continuing version, which should get involved in the neuroph project. -
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Aliza Gaming API
An extensible development framework for roleplay games.
AlizaGameAPI is a robust, open-source Java-based framework designed to streamline and enhance the development of 2D and 3D games. It offers a comprehensive set of tools, utilities, and libraries, empowering developers to create immersive and dynamic gaming experiences with ease. Key Features: Modular Architecture, Rich Graphics and UI Components, Comprehensive Game Logic and Character Management, Environment and World-Building Tools, Statistical and Mathematical Utilities, Enhanced Debugging... -
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Swarm Wars
Safety in numbers.
REPOSITORY MOVED TO GITHUB: https://github.com/happyjack27/SwarmWars video sample: http://youtu.be/s5mLNbdBQGY A game where you evolve & compete AI swarms. The organisms use swarm intelligence & ant colony optimization. The organisms can communicate through 3-color signaling as well as by laying beacons. They can attack and repair other organisms. They can select mates, and they can gather and distribute food and material. This behavior is controlled by a genetically evolved neural net... -
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PoleBalancing2D
Q-Learning Framework with example application
This is a small framework for Q(0) with a feedforward-neural net. The example application is a agent in 2D, which learns to balance a pole. -
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tmasterkey2
fuzzy and neural net software
NN and fuzzy combined written in lisp. -
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This project, npp (net plus plus, net++), is developed on top of open source package QuickNet for Neural Network training in speech recognition.
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Speedy Composer
Speedy Composer – Artificial Neural Network Melody Composer.
Thank you for your interest in Speedy Composer. Speedy Composer is an automated application for composing melodies for Speedy Net members. We recently made changes to the source code of Speedy Net, and converted it into the Python language and Django framework. Since Speedy Composer was originally written in PHP, it is not adapted to work with Speedy Net in its current form. So unfortunately we were forced to temporarily close the app Speedy Composer. But don't worry, we kept backups of all...