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},
   }

You might also like...
PyTorch framework, for reproducing experiments from the paper Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks
PyTorch framework, for reproducing experiments from the paper Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks

Implicit Regularization in Hierarchical Tensor Factorization and Deep Convolutional Neural Networks. Code, based on the PyTorch framework, for reprodu

This repository is related to an Arabic tutorial, within the tutorial we discuss the common data structure and algorithms and their worst and best case for each, then implement the code using Python.

Data Structure and Algorithms with Python This repository is related to the Arabic tutorial here, within the tutorial we discuss the common data struc

Python library containing BART query generation and BERT-based Siamese models for neural retrieval.
Python library containing BART query generation and BERT-based Siamese models for neural retrieval.

Neural Retrieval Embedding-based Zero-shot Retrieval through Query Generation leverages query synthesis over large corpuses of unlabeled text (such as

PyTorch CZSL framework containing GQA, the open-world setting, and the CGE and CompCos methods.
PyTorch CZSL framework containing GQA, the open-world setting, and the CGE and CompCos methods.

Compositional Zero-Shot Learning This is the official PyTorch code of the CVPR 2021 works Learning Graph Embeddings for Compositional Zero-shot Learni

A Planar RGB-D SLAM which utilizes Manhattan World structure to provide optimal camera pose trajectory while also providing a sparse reconstruction containing points, lines and planes, and a dense surfel-based reconstruction.
A Planar RGB-D SLAM which utilizes Manhattan World structure to provide optimal camera pose trajectory while also providing a sparse reconstruction containing points, lines and planes, and a dense surfel-based reconstruction.

ManhattanSLAM Authors: Raza Yunus, Yanyan Li and Federico Tombari ManhattanSLAM is a real-time SLAM library for RGB-D cameras that computes the camera

A toolkit for document-level event extraction, containing some SOTA model implementations
A toolkit for document-level event extraction, containing some SOTA model implementations

❤️ A Toolkit for Document-level Event Extraction with & without Triggers Hi, there 👋 . Thanks for your stay in this repo. This project aims at buildi

Google-drive-to-sqlite - Create a SQLite database containing metadata from Google Drive

google-drive-to-sqlite Create a SQLite database containing metadata from Google

Related resources for our EMNLP 2021 paper Plan-then-Generate: Controlled Data-to-Text Generation via Planning

Plan-then-Generate: Controlled Data-to-Text Generation via Planning Authors: Yixuan Su, David Vandyke, Sihui Wang, Yimai Fang, and Nigel Collier Code

Repo for the paper "DiLBERT: Cheap Embeddings for Disease Related Medical NLP"

DiLBERT Repo for the paper "DiLBERT: Cheap Embeddings for Disease Related Medical NLP" Pretrained Model The pretrained model presented in the paper is

Owner
Nethra Gunti
Django Development | Machine Learning | Data Analysis
Nethra Gunti
The LaTeX and Python code for generating the paper, experiments' results and visualizations reported in each paper is available (whenever possible) in the paper's directory

This repository contains the software implementation of most algorithms used or developed in my research. The LaTeX and Python code for generating the

João Fonseca 3 Jan 3, 2023
Generate vibrant and detailed images using only text.

CLIP Guided Diffusion From RiversHaveWings. Generate vibrant and detailed images using only text. See captions and more generations in the Gallery See

Clay M. 401 Dec 28, 2022
Python-experiments - A Repository which contains python scripts to automate things and make your life easier with python

Python Experiments A Repository which contains python scripts to automate things

Vivek Kumar Singh 11 Sep 25, 2022
Code to reproduce the experiments in the paper "Transformer Based Multi-Source Domain Adaptation" (EMNLP 2020)

Transformer Based Multi-Source Domain Adaptation Dustin Wright and Isabelle Augenstein To appear in EMNLP 2020. Read the preprint: https://arxiv.org/a

CopeNLU 36 Dec 5, 2022
Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax

Clockwork VAEs in JAX/Flax Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax, ported

Julius Kunze 26 Oct 5, 2022
Neural implicit reconstruction experiments for the Vector Neuron paper

Neural Implicit Reconstruction with Vector Neurons This repository contains code for the neural implicit reconstruction experiments in the paper Vecto

Congyue Deng 35 Jan 2, 2023
PyTorch implementation of the supervised learning experiments from the paper Model-Agnostic Meta-Learning (MAML)

pytorch-maml This is a PyTorch implementation of the supervised learning experiments from the paper Model-Agnostic Meta-Learning (MAML): https://arxiv

Kate Rakelly 516 Jan 5, 2023
Code to reproduce experiments in the paper "Explainability Requires Interactivity".

Explainability Requires Interactivity This repository contains the code to train all custom models used in the paper Explainability Requires Interacti

Digital Health & Machine Learning 5 Apr 7, 2022
Code to reproduce the experiments from our NeurIPS 2021 paper " The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective"

Code To run: python runner.py new --save <SAVE_NAME> --data <PATH_TO_DATA_DIR> --dataset <DATASET> --model <model_name> [options] --n 1000 - train - t

Geoff Pleiss 5 Dec 12, 2022