Autoencoders pretraining using clustering

Overview

DESCRIPTION:

Autoencoders pretraining using clustering.

v.1.0

Related to the work:

Improving Autoencoders Performance for Hyperspectral Unmixing using Clustering

Source code for the review process of the 14th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2022).

LICENSE:

Copyright 2021 Institute of Theoretical and Applied Informatics, Polish Academy of Sciences (ITAI PAS) https://www.iitis.pl Authors:

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.

FUNCTIONALITY:

  • Autoencoder training and evaluation for spectral unmixing task
  • Autoencoder pretraining using clustering algorithm

FILES:

  • ATE/*: Autoencoder Testing Environment files.
  • cfg/*: Config files.
  • grids/*.py: Files required to run comparison between baseline and pretraining-based autoencoder training.
  • grids/run_exp.sh: File to run comparison between baseline and pretraining-based autoencoder training.
  • grids/scripts/*: Simple scripts used for various purposes.
  • grids/tests/*: Unit tests.

DATASETS:

All datasets have to be inserted into ./ATE/data/ folder.

USAGE:

Run the script using ./grids/run_exp.sh file. The script requires Samson and Jasper datasets in the ./ATE/data/ folder as well as saved models' weights in mpath (set by default to ./models).

To run demo version of the experiment, run ./grids/run_exp_demo.sh file. The results of the experiment will be generated in the ./results directory. Please note that this version of the script uses Custom dataset which is composed of random numbers, so the results too are going to be random.

DEPENDENCIES

The scripts are dependent on Autoencoder Testing Environment. Used datasets, as well as loaded models' weights follow the same structure.

Owner
IITiS PAN
Institute of Theoretical and Applied Informatics, Polish Academy of Sciences
IITiS PAN
Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018

Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples This project is for the paper "Training Confidence-Calibrated Clas

168 Nov 29, 2022
Winning solution of the Indoor Location & Navigation Kaggle competition

This repository contains the code to generate the winning solution of the Kaggle competition on indoor location and navigation organized by Microsoft

Tom Van de Wiele 62 Dec 28, 2022
HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events globally on daily to subseasonal timescales.

HeatNet HeatNet is a python package that provides tools to build, train and evaluate neural networks designed to predict extreme heat wave events glob

Google Research 6 Jul 07, 2022
The repository forked from NVlabs uses our data. (Differentiable rasterization applied to 3D model simplification tasks)

nvdiffmodeling [origin_code] Differentiable rasterization applied to 3D model simplification tasks, as described in the paper: Appearance-Driven Autom

Qiujie (Jay) Dong 2 Oct 31, 2022
Simple Tensorflow implementation of "Adaptive Convolutions for Structure-Aware Style Transfer" (CVPR 2021)

AdaConv — Simple TensorFlow Implementation [Paper] : Adaptive Convolutions for Structure-Aware Style Transfer (CVPR 2021) Note This repository does no

Junho Kim 26 Nov 18, 2022
Deep-learning-roadmap - All You Need to Know About Deep Learning - A kick-starter

Deep Learning - All You Need to Know Sponsorship To support maintaining and upgrading this project, please kindly consider Sponsoring the project deve

Instill AI 4.4k Dec 26, 2022
SeqTR: A Simple yet Universal Network for Visual Grounding

SeqTR This is the official implementation of SeqTR: A Simple yet Universal Network for Visual Grounding, which simplifies and unifies the modelling fo

seanZhuh 76 Dec 24, 2022
Standalone pre-training recipe with JAX+Flax

Sabertooth Sabertooth is standalone pre-training recipe based on JAX+Flax, with data pipelines implemented in Rust. It runs on CPU, GPU, and/or TPU, b

Nikita Kitaev 26 Nov 28, 2022
AsymmetricGAN - Dual Generator Generative Adversarial Networks for Multi-Domain Image-to-Image Translation

AsymmetricGAN for Image-to-Image Translation AsymmetricGAN Framework for Multi-Domain Image-to-Image Translation AsymmetricGAN Framework for Hand Gest

Hao Tang 42 Jan 15, 2022
Training neural models with structured signals.

Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured

955 Jan 02, 2023
This repository collects 100 papers related to negative sampling methods.

Negative-Sampling-Paper This repository collects 100 papers related to negative sampling methods, covering multiple research fields such as Recommenda

RUCAIBox 119 Dec 29, 2022
ICCV2021 - Mining Contextual Information Beyond Image for Semantic Segmentation

Introduction The official repository for "Mining Contextual Information Beyond Image for Semantic Segmentation". Our full code has been merged into ss

55 Nov 09, 2022
Deep deconfounded recommender (Deep-Deconf) for paper "Deep causal reasoning for recommendations"

Deep Causal Reasoning for Recommender Systems The codes are associated with the following paper: Deep Causal Reasoning for Recommendations, Yaochen Zh

Yaochen Zhu 22 Oct 15, 2022
Official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution"

RealBasicVSR [Paper] This is the official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution, arXiv". This repository contain

Kelvin C.K. Chan 566 Dec 28, 2022
LBK 26 Dec 28, 2022
Official codebase used to develop Vision Transformer, MLP-Mixer, LiT and more.

Big Vision This codebase is designed for training large-scale vision models on Cloud TPU VMs. It is based on Jax/Flax libraries, and uses tf.data and

Google Research 701 Jan 03, 2023
Implementation of "With a Little Help from my Temporal Context: Multimodal Egocentric Action Recognition, BMVC, 2021" in PyTorch

Multimodal Temporal Context Network (MTCN) This repository implements the model proposed in the paper: Evangelos Kazakos, Jaesung Huh, Arsha Nagrani,

Evangelos Kazakos 13 Nov 24, 2022
Tensorflow AffordanceNet and AffContext implementations

AffordanceNet and AffContext This is tensorflow AffordanceNet and AffContext implementations. Both are implemented and tested with tensorflow 2.3. The

Beatriz Pérez 6 Dec 01, 2022
The code of "Dependency Learning for Legal Judgment Prediction with a Unified Text-to-Text Transformer".

Code data_preprocess.py: preprocess data for Dependent-T5. parameters.py: define parameters of Dependent-T5. train_tools.py: traning and evaluation co

1 Apr 21, 2022
Pytorch cuda extension of grid_sample1d

Grid Sample 1d pytorch cuda extension of grid sample 1d. Since pytorch only supports grid sample 2d/3d, I extend the 1d version for efficiency. The fo

lyricpoem 24 Dec 03, 2022