Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs

Overview

Implementation for the paper:

Probabilistic Entity Representation Model for Reasoning over Knowledge Graphs, Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian and Chandan Reddy, NeurIPS 2021.

Requirements

torch==1.2.0
tensorboardX==1.6

Run

To reproduce the results on FB15k-237, DRKG and NELL, the hyperparameters are set in example.sh.

bash run.sh

Arguments:

--do_train : Boolean that indicates if model should be trained
--cuda : Boolean that indicates if cuda should be used
--do_valid : Boolean that indicates if model should use validation
--do_test : Boolean that indicates if model should be tested to log metrics
--data_path : Folder that contains train, test and validation 
--model : Use 2-dimensions or one dimension for the model
-n : Number of negative samples per positive sample
-b : Batch size for training
-d : Dimension of embeddings (should be equal to semantic vector dimensions)
-lr : Learning rate of the model
--max_steps : Max number of epochs
--cpu_num : number of CPUs
--test_batch_size : Batch size for testing
--center_reg : Regularization factor for center updates
--geo : Gaussian embeddings or Vec embeddings
--task : Tasks for training
--stepsforpath : Same as number of epochs
--offset_deepsets : Aggregation methods for offsets
--center_deepsets : Aggregation methods for centers
--print_on_screen : Output should print on screen

Code details

dataloader.py - File to load data for the PERM models
model_gaussian.py - File with the model definition for the PERM model and baselines
main_gaussian.py - File to run the model for different experiments
Owner
Nurendra Choudhary
PhD Student
Nurendra Choudhary
Music Source Separation; Train & Eval & Inference piplines and pretrained models we used for 2021 ISMIR MDX Challenge.

Music Source Separation with Channel-wise Subband Phase Aware ResUnet (CWS-PResUNet) Introduction This repo contains the pretrained Music Source Separ

Lau 100 Dec 25, 2022
Aggragrating Nested Transformer Official Jax Implementation

NesT is a simple method, which aggragrates nested local transformers on image blocks. The idea makes vision transformers attain better accuracy, data efficiency, and convergence on the ImageNet bench

Google Research 169 Dec 20, 2022
Automate issue discovery for your projects against Lightning nightly and releases.

Automated Testing for Lightning EcoSystem Projects Automate issue discovery for your projects against Lightning nightly and releases. You get CPUs, Mu

Pytorch Lightning 41 Dec 24, 2022
This repository is an implementation of our NeurIPS 2021 paper (Stylized Dialogue Generation with Multi-Pass Dual Learning) in PyTorch.

MPDL---TODO This repository is an implementation of our NeurIPS 2021 paper (Stylized Dialogue Generation with Multi-Pass Dual Learning) in PyTorch. Ci

CodebaseLi 3 Nov 27, 2022
QICK: Quantum Instrumentation Control Kit

QICK: Quantum Instrumentation Control Kit The QICK is a kit of firmware and software to use the Xilinx RFSoC to control quantum systems. It consists o

81 Dec 15, 2022
A tight inclusion function for continuous collision detection

Tight-Inclusion Continuous Collision Detection A conservative Continuous Collision Detection (CCD) method with support for minimum separation. You can

Continuous Collision Detection 89 Jan 01, 2023
An Open-Source Toolkit for Prompt-Learning.

An Open-Source Framework for Prompt-learning. Overview • Installation • How To Use • Docs • Paper • Citation • What's New? Nov 2021: Now we have relea

THUNLP 2.3k Jan 07, 2023
Code for A Volumetric Transformer for Accurate 3D Tumor Segmentation

VT-UNet This repo contains the supported pytorch code and configuration files to reproduce 3D medical image segmentaion results of VT-UNet. Environmen

Himashi Amanda Peiris 114 Dec 20, 2022
Project of 'TBEFN: A Two-branch Exposure-fusion Network for Low-light Image Enhancement '

TBEFN: A Two-branch Exposure-fusion Network for Low-light Image Enhancement Codes for TMM20 paper "TBEFN: A Two-branch Exposure-fusion Network for Low

KUN LU 31 Nov 06, 2022
Transformer Huffman coding - Complete Huffman coding through transformer

Transformer_Huffman_coding Complete Huffman coding through transformer 2022/2/19

3 May 19, 2022
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.

Swin Transformer for Object Detection This repo contains the supported code and configuration files to reproduce object detection results of Swin Tran

Swin Transformer 1.4k Dec 30, 2022
A state-of-the-art semi-supervised method for image recognition

Mean teachers are better role models Paper ---- NIPS 2017 poster ---- NIPS 2017 spotlight slides ---- Blog post By Antti Tarvainen, Harri Valpola (The

Curious AI 1.4k Jan 06, 2023
This example implements the end-to-end MLOps process using Vertex AI platform and Smart Analytics technology capabilities

MLOps with Vertex AI This example implements the end-to-end MLOps process using Vertex AI platform and Smart Analytics technology capabilities. The ex

Google Cloud Platform 238 Dec 21, 2022
Simulations for Turring patterns on an apically expanding domain. T

Turing patterns on expanding domain Simulations for Turring patterns on an apically expanding domain. The details about the models and numerical imple

Yue Liu 0 Aug 03, 2021
Deep learning with dynamic computation graphs in TensorFlow

TensorFlow Fold TensorFlow Fold is a library for creating TensorFlow models that consume structured data, where the structure of the computation graph

1.8k Dec 28, 2022
Try out deep learning models online on Google Colab

Try out deep learning models online on Google Colab

Erdene-Ochir Tuguldur 1.5k Dec 27, 2022
ruptures: change point detection in Python

Welcome to ruptures ruptures is a Python library for off-line change point detection. This package provides methods for the analysis and segmentation

Charles T. 1.1k Jan 03, 2023
Weight estimation in CT by multi atlas techniques

maweight A Python package for multi-atlas based weight estimation for CT images, including segmentation by registration, feature extraction and model

György Kovács 0 Dec 24, 2021
Multi-Object Tracking in Satellite Videos with Graph-Based Multi-Task Modeling

TGraM Multi-Object Tracking in Satellite Videos with Graph-Based Multi-Task Modeling, Qibin He, Xian Sun, Zhiyuan Yan, Beibei Li, Kun Fu Abstract Rece

Qibin He 6 Nov 25, 2022