Topic: adam Goto Github
Some thing interesting about adam
Some thing interesting about adam
adam,ADAM - A Question Answering System. Inspired from IBM Watson
User: 5hirish
Home Page: http://www.shirishkadam.com/
adam,My profileπ
User: adam-mcdaniel
Home Page: https://adam-mcdaniel.net
adam,gradient descent optimization algorithms
User: alphadl
adam,implementation of neural network from scratch only using numpy (Conv, Fc, Maxpool, optimizers and activation functions)
User: amirrezarajabi
adam,Adam, NAdam and AAdam optimizers
User: angetato
adam,A Deep Learning and preprocessing framework in Rust with support for CPU and GPU.
User: anicetngrt
Home Page: https://linktr.ee/jironn
adam,Rethinking SWATS (Switches from Adam to SGD) Optimiser
User: anirudhmaiya
adam,Coding Assignment of PFN intern 2019
User: arahatashun
adam,DeepVariant-on-Spark is a germline short variant calling pipeline that runs Google DeepVariant on Apache Spark at scale.
Organization: atgenomix
adam,ADAM python client and notebooks
Organization: b612-asteroid-institute
adam,Orbit propagation, orbit determination, and analysis code
Organization: b612-asteroid-institute
adam,A tour of different optimization algorithms in PyTorch.
User: bentrevett
adam,RAdam implemented in Keras & TensorFlow
User: cyberzhg
Home Page: https://pypi.org/project/keras-rectified-adam/
adam,Easy-to-use AdaHessian optimizer (PyTorch)
User: davda54
adam,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.
Organization: echocat
Home Page: https://adam.echocat.org
adam,8-bit systems to ESP32 WiFi Multifunction Firmware
Organization: fujinetwifi
Home Page: https://fujinet.online
adam,AdamW optimizer for Keras
User: glambard
adam,A comparison between implementations of different gradient-based optimization algorithms (Gradient Descent, Adam, Adamax, Nadam, Amsgrad). The comparison was made on some of the most common functions used for testing optimization algorithms.
User: guyez
adam,[Python] [arXiv/cs] Paper "An Overview of Gradient Descent Optimization Algorithms" by Sebastian Ruder
User: harshraj11584
adam,Simple MATLAB toolbox for deep learning network: Version 1.0.3
User: hiroyuki-kasai
adam,"Simulations for the paper 'A Review Article On Gradient Descent Optimization Algorithms' by Sebastian Roeder"
User: jelhamm
Home Page: https://www.ruder.io/optimizing-gradient-descent/
adam,Quasi Hyperbolic Rectified DEMON Adam/Amsgrad with AdaMod, Gradient Centralization, Lookahead, iterative averaging and decorrelated Weight Decay
User: jrc1995
adam,Code for the CDISC {admiral} hackathon, Feb 2023. The objective of this hackathon is to develop ADaM datasets in R using the ADaM in R Asset Library {admiral} and other Pharmaverse packages.
User: liamhobby
adam,On the Variance of the Adaptive Learning Rate and Beyond
User: liyuanlucasliu
Home Page: https://arxiv.org/abs/1908.03265
adam,pytorch implement of NovoGrad Optimizer
User: lonepatient
adam,Adam (or adm) is a coroutine-friendly Android Debug Bridge client written in Kotlin
User: malinskiy
Home Page: https://malinskiy.github.io/adam/
adam,AdaShift optimizer implementation in PyTorch
User: mknbv
adam,Unofficial implementation of Switching from Adam to SGD optimization in PyTorch.
User: mrpatekful
adam,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
User: nasdin
adam, The optimization methods in deep learning explained by Vietnamese such as gradient descent, momentum, NAG, AdaGrad, Adadelta, RMSProp, Adam, Adamax, Nadam, AMSGrad.
User: nducthang
adam,Lion and Adam optimization comparison
User: nengwp
adam,Implementation of Deep Neural Network from scratch without other librariees
User: nikeshbajaj
Home Page: http://nikeshbajaj.in
adam,Literature survey of convex optimizers and optimisation methods for deep-learning; made especially for optimisation researchers with β€οΈ
Organization: optimalfoundation
adam,Easy-to-use linear and non-linear solver
Organization: polyfem
Home Page: https://polyfem.github.io
adam,ADAM is an actively developed CSPRNG inspired by ISAAC64
User: pre-eth
adam,Classification of data using neural networks β with back propagation (multilayer perceptron) and with counter propagation
User: quwarm
adam,This package provides access to the QuasiGrad solver, developed for the 3rd ARPA-E Grid Optimization (GO) Challenge.
User: samchevalier
Home Page: https://arxiv.org/pdf/2310.06650.pdf
adam,DNN classifiers for WDBC and Wine datasets.
User: sandeepsukumaran
adam,Comprehensive image classification for training multilayer perceptron (MLP), LeNet, LeNet5, conv2, conv4, conv6, VGG11, VGG13, VGG16, VGG19 with batch normalization, ResNet18, ResNet34, ResNet50, MobilNetV2 on MNIST, CIFAR10, CIFAR100, and ImageNet1K.
User: sdamadi
adam,Toy implementations of some popular ML optimizers using Python/JAX
User: shreyansh26
adam,Generalization of Adam, AdaMax, AMSGrad algorithms for PyTorch
User: sss135
adam,This is an implementation of Adam: A Method for Stochastic Optimization.
User: tak27
adam,Learning Rate Warmup in PyTorch
User: tony-y
Home Page: https://tony-y.github.io/pytorch_warmup/
adam,Tensorflow-Keras callback implementing arXiv 1712.07628
User: tr7200
Home Page: https://arxiv.org/abs/1712.07628
adam,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)
User: uclaml
Home Page: https://arxiv.org/abs/1806.06763
adam,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
User: yanaieliyahu
adam,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
User: zmyzheng
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Open source projects and samples from Microsoft.
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Data-Driven Documents codes.
China tencent open source team.