Interpretable Multivariate Time Series Forecasting with Temporal Attention Convolutional Neural Networks. - Leonardos Pantiskas; Kees Verstoep; Henri E. Bal (SSCI, 2020)

A Framework for Imbalanced Time-Series Forecasting. - Luis P. Silvestrin; Leonardos Pantiskas; Mark Hoogendoorn (LOD, 2021)

Taking ROCKET on an Efficiency Mission: Multivariate Time Series Classification with LightWaveS. - Leonardos Pantiskas; Kees Verstoep; Mark Hoogendoorn; Henri E. Bal (DCOSS, 2022)

An Empirical Evaluation of Multivariate Time Series Classification with Input Transformation across Different Dimensions. - Leonardos Pantiskas; Kees Verstoep; Mark Hoogendoorn; Henri E. Bal (ICMLA, 2022)

Channel-Adaptive Early Exiting Using Reinforcement Learning for Multivariate Time Series Classification. - Leonardos Pantiskas; Kees Verstoep; Mark Hoogendoorn; Henri E. Bal (ICMLA, 2023)

Reinforcement Learning-Guided Channel Selection Across Time for Multivariate Time Series Classification. - Leonardos Pantiskas; Kees Verstoep; Mark Hoogendoorn; Henri E. Bal (SSCI, 2023)

Multivariate Time Series Early Classification Across Channel and Time Dimensions. - Leonardos Pantiskas; Kees Verstoep; Mark Hoogendoorn; Henri E. Bal (CoRR, 2023)