Learning Generative State Space Models for Active Inference [PDF]
Frontiers in Computational Neuroscience, 2020 In this paper we investigate the active inference framework as a means to enable autonomous behavior in artificial agents. Active inference is a theoretical framework underpinning the way organisms act and observe in the real world.
Ozan Çatal +4 more
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Statistical analysis of organelle movement using state-space models [PDF]
Plant Methods, 2023 Background Organelle motility is essential for the correct cellular function of various eukaryotic cells. In plant cells, chloroplasts move towards the intracellular area irradiated by a weak light to maximise photosynthesis. To initiate this process, an
Haruki Nishio +2 more
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Quantifying spontaneous infant movements using state-space models [PDF]
Scientific ReportsOver the first few months after birth, the typical emergence of spontaneous, fidgety general movements is associated with later developmental outcomes.
E. Passmore +6 more
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LiteMamba-Synth: lightweight state space models for efficient 3T-to-7T MRI translation [PDF]
Frontiers in NeuroanatomyIntroductionThe superior clinical utility of 7T magnetic resonance imaging (MRI) is constrained by high acquisition costs and limited scanner availability.
Zhengrui Zhang +3 more
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Parameter-coupled state space models based on quasi-Gaussian fuzzy approximation [PDF]
Scientific ReportsThe accuracy of a fuzzy system’s approximation is closely tied to the performance of fuzzy control systems design, while this system’s interpretability depends on the description of a mechanical model using human language.
Yizhi Wang +5 more
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Modelling menstrual cycle length in athletes using state-space models [PDF]
Scientific Reports, 2021 The ability to predict an individual’s menstrual cycle length to a high degree of precision could help female athletes to track their period and tailor their training and nutrition correspondingly.
Thiago de Paula Oliveira +4 more
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Compute-in-memory implementation of state space models for event sequence processing [PDF]
Nature CommunicationsState space models have recently emerged as a powerful framework for long sequence processing, outperforming traditional methods on diverse benchmarks.
Xiaoyu Zhang +6 more
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High-dimensional linear state space models for dynamic microbial interaction networks. [PDF]
PLoS ONE, 2017 Medical researchers are increasingly interested in knowing how the complex community of micro-organisms living on human body impacts human health. Key to this is to understand how the microbes interact with each other.
Iris Chen +5 more
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Identification State Space models and some Time Series models [PDF]
المجلة العراقية للعلوم الاحصائية, 2021 In this research, a comparison of the identification process for time series models represented by ARIMA models was studied by identification several models and choosing the best model based on some statistical criteria and one of the dynamic models ...
Zina Asem, heyam Hayawi
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dynamichazard: Dynamic Hazard Models Using State Space Models
Journal of Statistical Software, 2021 The dynamichazard package implements state space models that can provide a computationally efficient way to model time-varying parameters in survival analysis. I cover the models and some of the estimation methods implemented in dynamichazard, apply them
Benjamin Christoffersen
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