Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification

Last update: Dec 06, 2022

Related tags

Overview

Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification

Introduction.

This package includes the python codes for implementing Temporal Alignment Prediction (TAP) in supervised learning and few-shot action recognition, described in

Bing Su and Ji-Rong Wen. "Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification" ICLR, 2022.

License & disclaimer.

The codes can be used for research purposes only. This package is strictly for non-commercial academic use only.
Usage

The "Supervised_Learning" folder contains codes for using TAP in supervised distance learning for sequence data.

The "Few_Shot_Learning" folder contains codes for using TAP in few-shot action recognition.

Please refer to the ReadMe files in the folds.
Citations

Please cite the following paper if you use the codes:

Bing Su and Ji-Rong Wen, "Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification", ICLR, 2022.

Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification

Related tags

Overview

Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification

Owner

Kaggle Tweet Sentiment Extraction Competition: 1st place solution (Dark of the Moon team)

Implementation of the Object Relation Transformer for Image Captioning

ml4ir: Machine Learning for Information Retrieval

Turns your machine learning code into microservices with web API, interactive GUI, and more.

A benchmark of data-centric tasks from across the machine learning lifecycle.

This is a Machine Learning model which predicts the presence of Diabetes in Patients

Graphsignal is a machine learning model monitoring platform.

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

MiniTorch - a diy teaching library for machine learning engineers

This repository contains the code to predict house price using Linear Regression Method

Simple Machine Learning Tool Kit

Neighbourhood Retrieval (Nearest Neighbours) with Distance Correlation.

A naive Bayes model for cancer classification using a set of documents

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

Implementation of K-Nearest Neighbors Algorithm Using PySpark

Climin is a Python package for optimization, heavily biased to machine learning scenarios

Titanic Traveller Survivability Prediction

Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows.

Bayesian Additive Regression Trees For Python

All-in-one web-based development environment for machine learning