Hidden Markov Models for Activity Detection in Atrial Fibrillation Electrograms. - Gonzalo Rios-Muñoz; Fernando Moreno-Pino; Nina Soto; Pablo M. Olmos; Antonio Artés-Rodríguez; Francisco Fernandez-Aviles; Angel Arenal (CinC, 2020)

PyHHMM: A Python Library for Heterogeneous Hidden Markov Models. - Fernando Moreno-Pino; Emese Sükei; Pablo M. Olmos; Antonio Artés-Rodríguez (CoRR, 2022)

DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutions. - Fernando Moreno-Pino; Stefan Zohren (CoRR, 2022)

Heterogeneous Hidden Markov Models for Sleep Activity Recognition from Multi-Source Passively Sensed Data. - Fernando Moreno-Pino; María Martínez-García; Pablo M. Olmos; Antonio Artés-Rodríguez (CoRR, 2022)

Sleep Activity Recognition and Characterization from Multi-Source Passively Sensed Data. - María Martínez-García; Fernando Moreno-Pino; Pablo M. Olmos; Antonio Artés-Rodríguez (CoRR, 2023)

Interpretable Spectral Variational AutoEncoder (ISVAE) for time series clustering. - Óscar Jiménez Rama; Fernando Moreno-Pino; David Ramírez; Pablo M. Olmos (CoRR, 2023)

Deep autoregressive models with spectral attention. - Fernando Moreno-Pino; Pablo M. Olmos; Antonio Artés-Rodríguez (Pattern Recognit., 2023)

Rough Transformers: Lightweight and Continuous Time Series Modelling through Signature Patching. - Fernando Moreno-Pino; Alvaro Arroyo; Harrison Waldon; Xiaowen Dong 001; Álvaro Cartea (NeurIPS, 2024)

Rough Transformers for Continuous and Efficient Time-Series Modelling. - Fernando Moreno-Pino; Alvaro Arroyo; Harrison Waldon; Xiaowen Dong 001; Álvaro Cartea (CoRR, 2024)

Rough Transformers: Lightweight Continuous-Time Sequence Modelling with Path Signatures. - Fernando Moreno-Pino; Alvaro Arroyo; Harrison Waldon; Xiaowen Dong 001; Álvaro Cartea (CoRR, 2024)