This is the repository of shape matching algorithm Iterative Rotations and Assignments (IRA)

Overview

Description

This is the repository of shape matching algorithm Iterative Rotations and Assignments (IRA), described in the publication [1].

Directory contents

/IRA: Contains the IRA software, see also the README in /IRA.

/benchmark_test: Contains data and other software used for benchmark tests from [1]. See also the README in /benchmark_test folder.

Compile and run

To run IRA, you need to compile it. See README in /IRA subdirectory.

References

[1] Gunde M., Salles N., Hemeryck A., Martin Samos L. IRA: A shape matching approach for recognition and comparison of generic atomic patterns, Journal of Chemical Information and Modeling (2021), DOI: https://doi.org/10.1021/acs.jcim.1c00567, HAL: hal-03406717, arXiv: 2111.00939

You might also like...
Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch
Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch

Perceiver - Pytorch Implementation of Perceiver, General Perception with Iterative Attention, in Pytorch Install $ pip install perceiver-pytorch Usage

Official Implementation for
Official Implementation for "ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement" https://arxiv.org/abs/2104.02699

ReStyle: A Residual-Based StyleGAN Encoder via Iterative Refinement Recently, the power of unconditional image synthesis has significantly advanced th

Implementation of Perceiver, General Perception with Iterative Attention in TensorFlow
Implementation of Perceiver, General Perception with Iterative Attention in TensorFlow

Perceiver This Python package implements Perceiver: General Perception with Iterative Attention by Andrew Jaegle in TensorFlow. This model builds on t

PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis
PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis

WaveGrad2 - PyTorch Implementation PyTorch Implementation of Google Brain's WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis. Status (202

Pytorch implementation of “Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement”

Graph-to-Graph Transformers Self-attention models, such as Transformer, have been hugely successful in a wide range of natural language processing (NL

StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking

StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking Datasets You can download datasets that have been pre-pr

Code for PackNet: Adding Multiple Tasks to a Single Network by Iterative Pruning

PackNet: https://arxiv.org/abs/1711.05769 Pretrained models are available here: https://uofi.box.com/s/zap2p03tnst9dfisad4u0sfupc0y1fxt Datasets in Py

[CVPR 2021] Official PyTorch Implementation for
[CVPR 2021] Official PyTorch Implementation for "Iterative Filter Adaptive Network for Single Image Defocus Deblurring"

IFAN: Iterative Filter Adaptive Network for Single Image Defocus Deblurring Checkout for the demo (GUI/Google Colab)! The GUI version might occasional

Unoffical implementation about Image Super-Resolution via Iterative Refinement by Pytorch
Unoffical implementation about Image Super-Resolution via Iterative Refinement by Pytorch

Image Super-Resolution via Iterative Refinement Paper | Project Brief This is a unoffical implementation about Image Super-Resolution via Iterative Re

Comments
  • ira_eq.x doesn't work.

    ira_eq.x doesn't work.

    Hi , @mgoonde .

    I am a student working on a project of Off-lattice Kinetic Monte Carlo. I found your paper and source code with excitement. As you mentioned in the paper(IRA: A shape matching approach for recognition and comparison of generic atomic patterns), in self-Learning KMC, atomic assignment is unknown amd number of atoms unset. Traditional optimal method like SVD and assignment method like Hungarian algorithm cannot work on my system. So I downloaded your code and tried.

    However, there was something wrong after I combined two .xyz system and executed ira_eq.x.

    First, variable hd_fin not defined. To be honest, I don't know what it means. So i changed hd_out = hd_fin to hd_out = hd image

    Second, the way you permute the coordinates is not recognized by my machine, it goes image , whenerver there is a permutation operation. So I changed it from coords1(:,:) = coords1(:,nint(d_o(2,:))) to do i = 1, nat1 coords1(:,i) = coords1_tmp(:,nint(d_o(2,i))) end do So does the array typ1/typ2/coords2

    After doing these rescue measures, I ran your example ./ira_eq.x < temp_ira. temp_ira is combined from benchmark_test/data/lj_clusters/xyz/47.xyz, same structure file in run_single.sh, and the randomized one. The two xyz structures didn't found scattered using ovito. The result goes infinity.

    I don't know what is wrong and I am not that farmiliar with fortran. So I appreciate your help about it. Best wishes.

    opened by FanMover 1
Releases(IRA_v1.5.0)
  • IRA_v1.5.0(May 12, 2022)

    The second release of IRA code. Improvements are made on performance (speed), and in the unification of routines dealing with equal and nonequal number of atoms. An interface to python is also added. For complete list of changes see the version_history file.

    Source code(tar.gz)
    Source code(zip)
  • v1.0.0(Nov 18, 2021)

Owner
MAMMASMIAS Consortium
Multiscale And Multi Model ApproacheS for Materials In Applied Science Consortium
MAMMASMIAS Consortium
Library for 8-bit optimizers and quantization routines.

bitsandbytes Bitsandbytes is a lightweight wrapper around CUDA custom functions, in particular 8-bit optimizers and quantization functions. Paper -- V

Facebook Research 687 Jan 04, 2023
An Open Source Machine Learning Framework for Everyone

Documentation TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, a

170.1k Jan 04, 2023
Finite Element Analysis

FElupe - Finite Element Analysis FElupe is a Python 3.6+ finite element analysis package focussing on the formulation and numerical solution of nonlin

Andreas D. 20 Jan 09, 2023
OpenDILab RL Kubernetes Custom Resource and Operator Lib

DI Orchestrator DI Orchestrator is designed to manage DI (Decision Intelligence) jobs using Kubernetes Custom Resource and Operator. Prerequisites A w

OpenDILab 205 Dec 29, 2022
Code for 1st place solution in Sleep AI Challenge SNU Hospital

Sleep AI Challenge SNU Hospital 2021 Code for 1st place solution for Sleep AI Challenge (Note that the code is not fully organized) Refer to the notio

Saewon Yang 13 Jan 03, 2022
A comprehensive and up-to-date developer education platform for Urbit.

curriculum A comprehensive and up-to-date developer education platform for Urbit. This project organizes developer capabilities into a hierarchy of co

Sigilante 36 Oct 04, 2022
Powerful unsupervised domain adaptation method for dense retrieval.

Powerful unsupervised domain adaptation method for dense retrieval

Ubiquitous Knowledge Processing Lab 191 Dec 28, 2022
Official Code Release for "CLIP-Adapter: Better Vision-Language Models with Feature Adapters"

Official Code Release for "CLIP-Adapter: Better Vision-Language Models with Feature Adapters" Pipeline of CLIP-Adapter CLIP-Adapter is a drop-in modul

peng gao 157 Dec 26, 2022
Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥

ElegantRL “小雅”: Scalable and Elastic Deep Reinforcement Learning ElegantRL is developed for researchers and practitioners with the following advantage

AI4Finance Foundation 2.5k Jan 05, 2023
Auto-Encoding Score Distribution Regression for Action Quality Assessment

DAE-AQA It is an open source program reference to paper Auto-Encoding Score Distribution Regression for Action Quality Assessment. 1.Introduction DAE

13 Nov 16, 2022
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction

This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se

Maha 490 Dec 15, 2022
Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations

Transfer-Learning-in-Reinforcement-Learning Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations Final Report Tra

Trung Hieu Tran 4 Oct 17, 2022
Subpopulation detection in high-dimensional single-cell data

PhenoGraph for Python3 PhenoGraph is a clustering method designed for high-dimensional single-cell data. It works by creating a graph ("network") repr

Dana Pe'er Lab 42 Sep 05, 2022
Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

Outlier Exposure This repository contains the essential code for the paper Deep Anomaly Detection with Outlier Exposure (ICLR 2019). Requires Python 3

Dan Hendrycks 464 Dec 27, 2022
GazeScroller - Using Facial Movements to perform Hands-free Gesture on the system

GazeScroller Using Facial Movements to perform Hands-free Gesture on the system

2 Jan 05, 2022
🐤 Nix-TTS: An Incredibly Lightweight End-to-End Text-to-Speech Model via Non End-to-End Distillation

🐤 Nix-TTS An Incredibly Lightweight End-to-End Text-to-Speech Model via Non End-to-End Distillation Rendi Chevi, Radityo Eko Prasojo, Alham Fikri Aji

Rendi Chevi 156 Jan 09, 2023
A pytorch reproduction of { Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation }.

A PyTorch Reproduction of HCN Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation. Ch

Guyue Hu 210 Dec 31, 2022
Vision-and-Language Navigation in Continuous Environments using Habitat

Vision-and-Language Navigation in Continuous Environments (VLN-CE) Project Website — VLN-CE Challenge — RxR-Habitat Challenge Official implementations

Jacob Krantz 132 Jan 02, 2023
利用yolov5和TensorRT从0到1实现目标检测的模型训练到模型部署全过程

写在前面 利用TensorRT加速推理速度是以时间换取精度的做法,意味着在推理速度上升的同时将会有精度的下降,不过不用太担心,精度下降微乎其微。此外,要有NVIDIA显卡,经测试,CUDA10.2可以支持20系列显卡及以下,30系列显卡需要CUDA11.x的支持,并且目前有bug。 默认你已经完成了

Helium 6 Jul 28, 2022
🧮 Matrix Factorization for Collaborative Filtering is just Solving an Adjoint Latent Dirichlet Allocation Model after All

Accompanying source code to the paper "Matrix Factorization for Collaborative Filtering is just Solving an Adjoint Latent Dirichlet Allocation Model A

Florian Wilhelm 39 Dec 03, 2022