Here are
24 public repositories
matching this topic...
🧠 Minimal implementations/tutorials of deep learning papers with side-by-side notes
Updated
Feb 1, 2021
Jupyter Notebook
A New Optimization Technique for Deep Neural Networks
Updated
Aug 18, 2020
Python
RAdam implemented in Keras & TensorFlow
Updated
Sep 25, 2019
Python
Keras/TF implementation of AdamW, SGDW, NadamW, Warm Restarts, and Learning Rate multipliers
Updated
Oct 26, 2020
Python
FrostNet: Towards Quantization-Aware Network Architecture Search
Updated
Nov 30, 2020
Python
Lookahead mechanism for optimizers in Keras.
Updated
Sep 23, 2019
Python
Neutron: A pytorch based implementation of Transformer and its variants.
Updated
Jan 20, 2021
Python
Accelerated tensor operations and dynamic neural networks based on reverse mode automatic differentiation for every device that can run Swift - from watchOS to Linux
Updated
Nov 27, 2020
Swift
Neural Network optimizers implemented from scratch in numpy (Adam, Adadelta, RMSProp, SGD, etc.)
Updated
Mar 21, 2020
Jupyter Notebook
A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
Updated
Dec 29, 2020
Python
Improved Hypergradient optimizers, providing better generalization and faster convergence.
Updated
Feb 27, 2020
Jupyter Notebook
Package for CGD and ACGD optimizers
Updated
Dec 16, 2020
Python
A Repository to Visualize the training of Linear Model by optimizers such as SGD, Adam, RMSProp, AdamW, ASMGrad etc
Updated
Aug 1, 2020
Jupyter Notebook
A curated list of optimizers for machine learning.
A collection of optimizers, some arcane others well known, for Flax.
Updated
Nov 17, 2020
Python
A set of NBA optimizers and GPP tools to help you win daily fantasy sports
Updated
Jan 21, 2021
Python
This is an application for showing how optimization algorithms work
Updated
Aug 11, 2020
Python
Neural Networks and optimizers from scratch in NumPy, featuring newer optimizers such as DemonAdam or QHAdam.
Updated
Dec 3, 2020
Jupyter Notebook
Evaluating optimization algorithms in IVHD method (interactive visualization of high-dimensional data)
ConvNN is used to predict digits for the MNIST dataset
Updated
Aug 15, 2020
Jupyter Notebook
A bridge from call back to iterator Acronym: bluesky callback iterator bridge. Motivated that bluesky wants to iterate over plans while solvers typically use call backs
Updated
Nov 12, 2020
Python
This is a reposatory for implementation of different types of optimizers (SGD, RMSprop, Adam etc.) with three different use cases Function Approximation, Multi-class Single-label Classification and Multi-class Multi-label Classification)
Updated
Jul 9, 2020
Jupyter Notebook
Neural networks framework built from scratch on Python.
Updated
Aug 15, 2020
Python
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