60 Open source projects that are alternatives of or similar to nibbler

Explore the energy-efficient dataflow scheduling for neural networks.

Free Tracks Optimizer Online Service

Code Deobfuscator

A tool to automate and optimize DraftKings and FanDuel lineup construction.

Scour - An SVG Optimizer / Cleaner

A library for portfolio optimization algorithms with python interface.

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning

👩 Pytorch and Jax code for the Madam optimiser.

🔩 Framework and Java implementation of the Alternating Variable Method

Add gradient noise to any Keras optimizer

Stratum <-> Stratum Proxy and optimizer for ethminer

AdamP: Slowing Down the Slowdown for Momentum Optimizers on Scale-invariant Weights (ICLR 2021)

A post-installation batch script for Windows

torch-optimizer -- collection of optimizers for Pytorch

Go to MIPS compiler, written in Go. Course project for Compiler Design (CS335).

Easily optimize images using WP CLI

The only storage saving app that actually works! :D

AdamW optimizer for Keras

Implementation for the paper "Latent Weights Do Not Exist: Rethinking Binarized Neural Network Optimization"

Linux System Optimizer and Monitoring - https://oguzhaninan.github.io/Stacer-Web

Adam, NAdam and AAdam optimizers

Virtual-machine Translation Intermediate Language

Lookahead optimizer ("Lookahead Optimizer: k steps forward, 1 step back") for tensorflow

SAM: Sharpness-Aware Minimization (PyTorch)

🛠 Versatile tool to optimize Windows

Over-engineered Brainfuck optimizing compiler and interpreter

lookahead optimizer (Lookahead Optimizer: k steps forward, 1 step back) for pytorch

Easy-to-use AdaHessian optimizer (PyTorch)

On the Variance of the Adaptive Learning Rate and Beyond

A WordPress cleanup and performance optimization plugin.

Easily optimize images using PHP

Implements https://arxiv.org/abs/1711.05101 AdamW optimizer, cosine learning rate scheduler and "Cyclical Learning Rates for Training Neural Networks" https://arxiv.org/abs/1506.01186 for PyTorch framework

An implementation of React v15.x that optimizes for small script size

A PyTorch implementation of Sharpness-Aware Minimization for Efficiently Improving Generalization

pytorch implement of Lookahead Optimizer

A development environment for robust and global optimization

Keras implementation of AdaBound

Community repository, to improve security and performance of Windows 10 and windows 11 with tweaks, commands, scripts, registry keys, configuration, tutorials and more

GLSL optimizer based on Mesa's GLSL compiler. Used to be used in Unity for mobile shader optimization.

SQL optimizer and rewriter. - SQL 优化、重写器(辅助 SQL 调优)。

Videos of deep learning optimizers moving on 3D problem-landscapes

SQL Optimizer And Rewriter

JHC Haskell compiler split into reusable components

Gradient accumulation for Keras

Merged into Gifsicle!

PostCss plugin to minify your CSS with clean-css

System Optimizer and Monitoring, Security Auditing, Vulnerability scanner for Linux, macOS, and UNIX-based systems

LAMB Optimizer for Large Batch Training (TensorFlow version)

lightweight lossless file minifier/optimizer

Go (golang) bindings for Picosat, the satisfiability solver

Heimer is a simple cross-platform mind map, diagram, and note-taking tool written in Qt.

PyTorch Impl. of Prediction Optimizer (to stabilize GAN training)

🚀Optimizer for mobile applications

An optimizer that trains as fast as Adam and as good as SGD in Tensorflow

horoscope is an optimizer inspector for DBMS.

A library to generate buildings from local urban regulations.

Convenient hyperparameter optimization

Go evolutionary algorithm is a computer library for developing evolutionary and genetic algorithms to solve optimisation problems with (or not) many constraints and many objectives. Also, a goal is to handle mixed-type representations (reals and integers).

A ToyDB (for beginner) based on MIT 6.830 and CMU 15445

The PyTorch Implementation of Variable Optimizers/ Neural Variable Risk Minimization proposed in our Neural Computation paper: Artificial Neural Variability for Deep Learning: On overfitting, Noise Memorization, and Catastrophic Forgetting.