Repository containing detailed experiments related to the paper "Memotion Analysis through the Lens of Joint Embedding".

Overview

Memotion Analysis Through The Lens Of Joint Embedding

This repository contains the experiments conducted as described in the paper 'Memotion Analysis through the Lens Of Joint Embedding'. This paper has been accepted for a poster presentation in the AAAI Student Abstract and Poster Program (SA-22).

Motivation

Visualisation

File Description

  • base_models: contains code used for training the reference models.

  • taskA: contains experiments related to Task A (sentiment analysis).

  • taskB: contains experiments related to Task B (emotion classification).

  • taskC: contains experiments related to Task C (semantic sub-classification of emotion).

For details about individual files, refer to the respective folders.

Reference

If you find this repo useful, please cite our paper:

    @inproceedings{gunti-etal-memotion,
    title = {Memotion Analysis through the Lens of Joint Embedding},
    author = {Nethra Gunti and  Sathyanarayanan Ramamoorthy and Parth Patwa and Amitava Das}
    booktitle =  {Proceedings of the AAAI Conference on Artificial Intelligence},
    year = {2022},
   }

Owner
Nethra Gunti
Django Development | Machine Learning | Data Analysis
Nethra Gunti
Code for Graph-to-Tree Learning for Solving Math Word Problems (ACL 2020)

Graph-to-Tree Learning for Solving Math Word Problems PyTorch implementation of Graph based Math Word Problem solver described in our ACL 2020 paper G

Jipeng Zhang 66 Nov 23, 2022
clustering moroccan stocks time series data using k-means with dtw (dynamic time warping)

Moroccan Stocks Clustering Context Hey! we don't always have to forecast time series am I right ? We use k-means to cluster about 70 moroccan stock pr

Ayman Lafaz 7 Oct 18, 2022
Torch-based tool for quantizing high-dimensional vectors using additive codebooks

Trainable multi-codebook quantization This repository implements a utility for use with PyTorch, and ideally GPUs, for training an efficient quantizer

Daniel Povey 41 Jan 07, 2023
Official implementation of Influence-balanced Loss for Imbalanced Visual Classification in PyTorch.

Official implementation of Influence-balanced Loss for Imbalanced Visual Classification in PyTorch.

Seulki Park 70 Jan 03, 2023
MAVE: : A Product Dataset for Multi-source Attribute Value Extraction

The dataset contains 3 million attribute-value annotations across 1257 unique categories on 2.2 million cleaned Amazon product profiles. It is a large, multi-sourced, diverse dataset for product attr

Google Research Datasets 89 Jan 08, 2023
Code for Deep Single-image Portrait Image Relighting

Deep Single-Image Portrait Relighting [Project Page] Hao Zhou, Sunil Hadap, Kalyan Sunkavalli, David W. Jacobs. In ICCV, 2019 Overview Test script for

438 Jan 05, 2023
Differentiable Factor Graph Optimization for Learning Smoothers @ IROS 2021

Differentiable Factor Graph Optimization for Learning Smoothers Overview Status Setup Datasets Training Evaluation Acknowledgements Overview Code rele

Brent Yi 60 Nov 14, 2022
Pytorch implementation of 'Fingerprint Presentation Attack Detector Using Global-Local Model'

RTK-PAD This is an official pytorch implementation of 'Fingerprint Presentation Attack Detector Using Global-Local Model', which is accepted by IEEE T

6 Aug 01, 2022
DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference

DeeBERT This is the code base for the paper DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference. Code in this repository is also available

Castorini 132 Nov 14, 2022
Python scripts for performing stereo depth estimation using the HITNET Tensorflow model.

HITNET-Stereo-Depth-estimation Python scripts for performing stereo depth estimation using the HITNET Tensorflow model from Google Research. Stereo de

Ibai Gorordo 76 Jan 02, 2023
Dataset and codebase for NeurIPS 2021 paper: Exploring Forensic Dental Identification with Deep Learning

Repository under construction. Example dataset, checkpoints, and training/testing scripts will be avaible soon! 💡 Collated best practices from most p

4 Jun 26, 2022
Machine Translation Implement By Bi-GRU And Transformer

Seq2Seq Translation Implement By Bidirectional GRU And Transformer In Pytorch Before You Run The Code You should download the data through the link be

He Wang 2 Oct 27, 2021
Rohit Ingole 2 Mar 24, 2022
This is a package for LiDARTag, described in paper: LiDARTag: A Real-Time Fiducial Tag System for Point Clouds

LiDARTag Overview This is a package for LiDARTag, described in paper: LiDARTag: A Real-Time Fiducial Tag System for Point Clouds (PDF)(arXiv). This wo

University of Michigan Dynamic Legged Locomotion Robotics Lab 159 Dec 21, 2022
Human annotated noisy labels for CIFAR-10 and CIFAR-100.

Dataloader for CIFAR-N CIFAR-10N noise_label = torch.load('./data/CIFAR-10_human.pt') clean_label = noise_label['clean_label'] worst_label = noise_lab

<a href=[email protected]"> 117 Nov 30, 2022
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation

Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation. Generally, MAS methods register multiple atlases, i.e., medical images with corresponding labels, to a target i

NanYoMy 13 Oct 09, 2022
Adversarial Color Enhancement: Generating Unrestricted Adversarial Images by Optimizing a Color Filter

ACE Please find the preliminary version published at BMVC 2020 in the folder BMVC_version, and its extended journal version in Journal_version. Datase

28 Dec 25, 2022
This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our paper "Accounting for Gaussian Process Imprecision in Bayesian Optimization"

Prior-RObust Bayesian Optimization (PROBO) Introduction, TOC This repository contains Prior-RObust Bayesian Optimization (PROBO) as introduced in our

Julian Rodemann 2 Mar 19, 2022
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W

Jungbeom Lee 81 Dec 16, 2022
Código de um painel de auto atendimento feito em Python.

Painel de Auto-Atendimento O intuito desse projeto era fazer em Python um programa que simulasse um painel de auto atendimento, no maior estilo Mac Do

Calebe Alves Evangelista 2 Nov 09, 2022