Pytorch implementation of Learning Rate Dropout.

Last update: Nov 25, 2022

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Deep Learning Learning-Rate-Dropout

Overview

Learning-Rate-Dropout

Pytorch implementation of Learning Rate Dropout.

Paper Link: https://arxiv.org/pdf/1912.00144.pdf

Train ResNet-34 for Cifar10:

run:

python main.py --model=resnet --optim=adam_lrd --lr=0.001 --LRD_p=0.5

python main.py --model=resnet --optim=adam --lr=0.001

python main.py --model=resnet --optim=sgd_lrd --lr=0.1 --LRD_p=0.5

python main.py --model=resnet --optim=sgd --lr=0.1 

python main.py --model=resnet --optim=rmsprop_lrd --lr=0.001 --LRD_p=0.5

python main.py --model=resnet --optim=rmsprop --lr=0.001

After training, run "plot.py" to show the learning curves.

Owner

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Pytorch implementation of Learning Rate Dropout.

Related tags

Overview

Learning-Rate-Dropout

Owner

Head and Neck Tumour Segmentation and Prediction of Patient Survival Project

Minimalistic PyTorch training loop

Activity image-based video retrieval

Implementation of the ALPHAMEPOL algorithm, presented in Unsupervised Reinforcement Learning in Multiple Environments.

DivNoising is an unsupervised denoising method to generate diverse denoised samples for any noisy input image. This repository contains the code to reproduce the results reported in the paper https://openreview.net/pdf?id=agHLCOBM5jP

Chinese named entity recognization with BiLSTM using Keras

CrossMLP - The repository offers the official implementation of our BMVC 2021 paper (oral) in PyTorch.

pyhsmm - library for approximate unsupervised inference in Bayesian Hidden Markov Models (HMMs) and explicit-duration Hidden semi-Markov Models (HSMMs), focusing on the Bayesian Nonparametric extensions, the HDP-HMM and HDP-HSMM, mostly with weak-limit approximations.

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Source code for "OmniPhotos: Casual 360° VR Photography"

Code for our ICCV 2021 Paper "OadTR: Online Action Detection with Transformers".

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