There are 8 repositories under optimizers topic.
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
🦁 Lion, new optimizer discovered by Google Brain using genetic algorithms that is purportedly better than Adam(w), in Pytorch
🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
A New Optimization Technique for Deep Neural Networks
RAdam implemented in Keras & TensorFlow
Keras/TF implementation of AdamW, SGDW, NadamW, Warm Restarts, and Learning Rate multipliers
Instantly improve your training performance of TensorFlow models with just 2 lines of code!
Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux
Code for the paper "Facial Emotion Recognition: State of the Art Performance on FER2013"
Summarize Massive Datasets using Submodular Optimization
Neutron: A pytorch based implementation of Transformer and its variants.
Neural Network optimizers implemented from scratch in numpy (Adam, Adadelta, RMSProp, SGD, etc.)
Intergration to get optimizers information from the SolarEdge portal
Fast, Modern, Memory Efficient, and Low Precision PyTorch Optimizers
Toy implementations of some popular ML optimizers using Python/JAX
A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
A collection of optimizers, some arcane others well known, for Flax.
Improved Hypergradient optimizers, providing better generalization and faster convergence.
A set of NBA optimizers and GPP tools to help you win daily fantasy sports
Lion - EvoLved Sign Momentum w/ New Optimizer API in TensorFlow 2.11+
Optimizers for/and sklearn compatible Machine Learning models
A curated list of optimizers for machine learning.
D2 is a strongly-typed, statically-typed, (mostly) inferred-type compiled language.
A Repository to Visualize the training of Linear Model by optimizers such as SGD, Adam, RMSProp, AdamW, ASMGrad etc
Neural Networks and optimizers from scratch in NumPy, featuring newer optimizers such as DemonAdam or QHAdam.
Lua-Based Machine, Deep And Reinforcement Learning Library (For Roblox And Pure Lua). Contains 34 Models!
Implementation and comparison of zero order vs first order method on the AdaMM (aka AMSGrad) optimizer: analysis of convergence rates and minima shape
Aplicação Windows desenvolvida por mim para otimização tanto do sistema como de certos jogos
dm-haiku implementation of hyperbolic neural networks
This repository is a meticulously assembled anthology of optimization algorithms, meticulously implemented in PyTorch, designed to cater to the diverse needs of the machine learning research community.