adam

On the Variance of the Adaptive Learning Rate and Beyond

ADAM - A Question Answering System. Inspired from IBM Watson

RAdam implemented in Keras & TensorFlow

Adam (or adm) is a coroutine-friendly Android Debug Bridge client written in Kotlin

This is a repo for my master thesis research about the Fusion of Visual SLAM and GPS. It contains the research paper, code and other interesting data.

Learning Rate Warmup in PyTorch

Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games

AdamW optimizer for Keras

ADAS is short for Adaptive Step Size, it's an optimizer that unlike other optimizers that just normalize the derivative, it fine-tunes the step size, truly making step size scheduling obsolete, achieving state-of-the-art training performance

Easy-to-use AdaHessian optimizer (PyTorch)

Unofficial implementation of Switching from Adam to SGD optimization in PyTorch.

A tour of different optimization algorithms in PyTorch.

Partially Adaptive Momentum Estimation method in the paper "Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks" (accepted by IJCAI 2020)

Toy implementations of some popular ML optimizers using Python/JAX

ColecoVision emulator for macOS, Raspberry Pi, Windows, Linux, BSD and RetroArch.

Deep learning projects including applications (face recognition, neural style transfer, autonomous driving, sign language reading, music generation, translation, speech recognition and NLP) and theories (CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, hyperparameter tuning, regularization, optimization, Residual Networks). Deep Learning Specialization by Andrew Ng, deeplearning.ai

Adam, NAdam and AAdam optimizers

[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder

Quasi Hyperbolic Rectified DEMON Adam/Amsgrad with AdaMod, Gradient Centralization, Lookahead, iterative averaging and decorrelated Weight Decay

Simple MATLAB toolbox for deep learning network: Version 1.0.3

AdaShift optimizer implementation in PyTorch

Addon which enhances all user profiles of confluence. It also adds an advanced people directory. The whole addon is configurable by means of an XML, can be localized, supports Velocity templates and supports view and edit restrictions.

pytorch implement of NovoGrad Optimizer

ADAM python client and notebooks

DeepVariant-on-Spark is a germline short variant calling pipeline that runs Google DeepVariant on Apache Spark at scale.

The optimization methods in deep learning explained by Vietnamese such as gradient descent, momentum, NAG, AdaGrad, Adadelta, RMSProp, Adam, Adamax, Nadam, AMSGrad.

Orbit propagation, orbit determination, and analysis code

Gradient descent optimizers for linear regression

Coding Assignment of PFN intern 2019