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
Fine-grained Post-training for Improving Retrieval-based Dialogue Systems - NAACL 2021

Fine-grained Post-training for Multi-turn Response Selection Implements the model described in the following paper Fine-grained Post-training for Impr

Janghoon Han 83 Dec 20, 2022
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners

DART Implementation for ICLR2022 paper Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners. Environment

ZJUNLP 83 Dec 27, 2022
TabNet for fastai

TabNet for fastai This is an adaptation of TabNet (Attention-based network for tabular data) for fastai (=2.0) library. The original paper https://ar

Mikhail Grankin 116 Oct 21, 2022
A library of multi-agent reinforcement learning components and systems

Mava: a research framework for distributed multi-agent reinforcement learning Table of Contents Overview Getting Started Supported Environments System

InstaDeep Ltd 463 Dec 23, 2022
DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection

DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Object Detection Code for our Paper DAFNe: A One-Stage Anchor-Free Deep Model for Oriented Obje

Steven Lang 58 Dec 19, 2022
Rank 1st in the public leaderboard of ScanRefer (2021-03-18)

InstanceRefer InstanceRefer: Cooperative Holistic Understanding for Visual Grounding on Point Clouds through Instance Multi-level Contextual Referring

63 Dec 07, 2022
Code accompanying "Adaptive Methods for Aggregated Domain Generalization"

Adaptive Methods for Aggregated Domain Generalization (AdaClust) Official Pytorch Implementation of Adaptive Methods for Aggregated Domain Generalizat

Xavier Thomas 15 Sep 20, 2022
This application is the basic of automated online-class-joiner(for YıldızEdu) within the right time. Gets the ZOOM link by scheduled date and time.

This application is the basic of automated online-class-joiner(for YıldızEdu) within the right time. Gets the ZOOM link by scheduled date and time.

215355 1 Dec 16, 2021
Creating multimodal multitask models

Fusion Brain Challenge The English version of the document can be found here. Обновления 01.11 Мы выкладываем пример данных, аналогичных private test

Sber AI 43 Nov 28, 2022
The Python code for the paper A Hybrid Quantum-Classical Algorithm for Robust Fitting

About The Python code for the paper A Hybrid Quantum-Classical Algorithm for Robust Fitting The demo program was only tested under Conda in a standard

Anh-Dzung Doan 5 Nov 28, 2022
This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes.

Rotate-Yolov5 This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes. Section I. Description The codes are

xinzelee 90 Dec 13, 2022
Аналитика доходности инвестиционного портфеля в Тинькофф брокере

Аналитика доходности инвестиционного портфеля Тиньков Видео на YouTube Для работы скрипта нужно установить три переменных окружения: export TINKOFF_TO

Alexey Goloburdin 64 Dec 17, 2022
A library for efficient similarity search and clustering of dense vectors.

Faiss Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any

Meta Research 18.8k Jan 08, 2023
As-ViT: Auto-scaling Vision Transformers without Training

As-ViT: Auto-scaling Vision Transformers without Training [PDF] Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wang, Denny Zhou In ICLR 2

VITA 68 Sep 05, 2022
Official Implement of CVPR 2021 paper “Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting”

RGBT Crowd Counting Lingbo Liu, Jiaqi Chen, Hefeng Wu, Guanbin Li, Chenglong Li, Liang Lin. "Cross-Modal Collaborative Representation Learning and a L

37 Dec 08, 2022
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)

PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering Jang Hyun Cho1, Utkarsh Mall2, Kavita Bala2, Bharath Harihar

Jang Hyun Cho 164 Dec 30, 2022
Code for "Neural 3D Scene Reconstruction with the Manhattan-world Assumption" CVPR 2022 Oral

News 05/10/2022 To make the comparison on ScanNet easier, we provide all quantitative and qualitative results of baselines here, including COLMAP, COL

ZJU3DV 365 Dec 30, 2022
The implementation of "Optimizing Shoulder to Shoulder: A Coordinated Sub-Band Fusion Model for Real-Time Full-Band Speech Enhancement"

SF-Net for fullband SE This is the repo of the manuscript "Optimizing Shoulder to Shoulder: A Coordinated Sub-Band Fusion Model for Real-Time Full-Ban

Guochen Yu 36 Dec 02, 2022
PyTorch package for the discrete VAE used for DALL·E.

Overview [Blog] [Paper] [Model Card] [Usage] This is the official PyTorch package for the discrete VAE used for DALL·E. Installation Before running th

OpenAI 9.5k Jan 05, 2023