3 citations · 8 across the 10 of their papers we have counts for
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Heterogeneous Hidden Markov Models for Sleep Activity Recognition from Multi-Source Passively Sensed Data
Fernando Moreno-Pino, María Martínez-García, Pablo M. Olmos +1
Psychiatric patients' passive activity monitoring is crucial to detect behavioural shifts in real-time, comprising a tool that helps clinicians supervise patients' evolution over t…
DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutions
Fernando Moreno-Pino, Stefan Zohren
Volatility forecasts play a central role among equity risk measures. Besides traditional statistical models, modern forecasting techniques based on machine learning can be employed…
PyHHMM: A Python Library for Heterogeneous Hidden Markov Models
Fernando Moreno-Pino, Emese Sükei, Pablo M. Olmos +1
We introduce PyHHMM, an object-oriented open-source Python implementation of Heterogeneous-Hidden Markov Models (HHMMs). In addition to HMM's basic core functionalities, such as di…