12 citations · 23 across the 11 of their papers we have counts for
11 papers
The Multiverse of Time Series Machine Learning: an Archive for Multivariate Time Series Classification
Matthew Middlehurst, Aiden Rushbrooke, Ali Ismail-Fawaz +6
Time series machine learning (TSML) is a growing research field that spans a wide range of tasks. The popularity of established tasks such as classification, clustering, and extrin…
Adaptive Structured Pruning of Convolutional Neural Networks for Time Series Classification
Javidan Abdullayev, Maxime Devanne, Cyril Meyer +3
Deep learning models for Time Series Classification (TSC) have achieved strong predictive performance but their high computational and memory requirements often limit deployment on…
Enhancing Time Series Classification with Diversity-Driven Neural Network Ensembles
Javidan Abdullayev, Maxime Devanne, Cyril Meyer +3
Ensemble methods have played a crucial role in achieving state-of-the-art (SOTA) performance across various machine learning tasks by leveraging the diversity of features learned b…
A Standardized Benchmark for Skeleton-Based Rehabilitation Assessment Using Deep Learning
Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti +2
Automated assessment of human motion plays a vital role in rehabilitation, enabling objective evaluation of patient performance and progress. Unlike general human activity recognit…
Deep Learning For Time Series Analysis With Application On Human Motion
Ali Ismail-Fawaz
Time series data, defined by equally spaced points over time, is essential in fields like medicine, telecommunications, and energy. Analyzing it involves tasks such as classificati…
Look Into the LITE in Deep Learning for Time Series Classification
Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti +2
Deep learning models have been shown to be a powerful solution for Time Series Classification (TSC). State-of-the-art architectures, while producing promising results on the UCR an…
aeon: a Python toolkit for learning from time series
Matthew Middlehurst, Ali Ismail-Fawaz, Antoine Guillaume +8
aeon is a unified Python 3 library for all machine learning tasks involving time series. The package contains modules for time series forecasting, classification, extrinsic regress…
Establishing a Unified Evaluation Framework for Human Motion Generation: A Comparative Analysis of Metrics
Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti +2
The development of generative artificial intelligence for human motion generation has expanded rapidly, necessitating a unified evaluation framework. This paper presents a detailed…
Finding Foundation Models for Time Series Classification with a PreText Task
Ali Ismail-Fawaz, Maxime Devanne, Stefano Berretti +2
Over the past decade, Time Series Classification (TSC) has gained an increasing attention. While various methods were explored, deep learning - particularly through Convolutional N…
ShapeDBA: Generating Effective Time Series Prototypes using ShapeDTW Barycenter Averaging
Ali Ismail-Fawaz, Hassan Ismail Fawaz, François Petitjean +5
Time series data can be found in almost every domain, ranging from the medical field to manufacturing and wireless communication. Generating realistic and useful exemplars and prot…
An Approach to Multiple Comparison Benchmark Evaluations that is Stable Under Manipulation of the Comparate Set
Ali Ismail-Fawaz, Angus Dempster, Chang Wei Tan +8
The measurement of progress using benchmarks evaluations is ubiquitous in computer science and machine learning. However, common approaches to analyzing and presenting the results…