7 papers · 1 filter
Enhancing deep learning models for time series classification via knowledge distillation
Javidan Abdullayev, Maxime Devanne, Jonathan Weber +1
Deep learning has achieved remarkable success in various domains including time series analysis, computer vision and natural language processing. However, high computational and me…
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…
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…
The impact of data set similarity and diversity on transfer learning success in time series forecasting
Claudia Ehrig, Benedikt Sonnleitner, Ursula Neumann +2
Pre-trained models have become pivotal in enhancing the efficiency and accuracy of time series forecasting on target data sets by leveraging transfer learning. While benchmarks val…