hidden Markov model
PulseAugur coverage of hidden Markov model — every cluster mentioning hidden Markov model across labs, papers, and developer communities, ranked by signal.
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New Bayesian Model Speeds Up Stellar Flare Detection
Researchers have developed a novel framework for Bayesian time-series modeling using Gaussian Processes (GPs) that significantly reduces computational costs. This new method employs a Variational Autoencoder (VAE) to le…
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New deFOREST Pipeline Fuses Satellite Data for Advanced Deforestation Detection
Researchers have developed a new deforestation detection pipeline called deFOREST that fuses optical and radar satellite data for enhanced sensing. The system constructs anomaly maps from optical data using a discrete K…
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New framework FlowMSM identifies causal structures in non-stationary time series
Researchers have developed a new framework called FlowMSM to address the challenges of identifying latent regimes and causal structures in non-stationary time series data. This framework is designed to handle complex dy…
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New C++ library libhmm offers accurate HMM parameter estimation
A new C++20 library called libhmm has been developed for Hidden Markov Models (HMMs), addressing a lack of well-maintained, embeddable C++ HMM software. It corrects the common use of approximations in the Baum-Welch alg…
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New framework analyzes transformer internal state dynamics
Researchers have developed a new framework called Markovian Circuit Tracing (MCT) to analyze the internal state dynamics of transformer models. This method uses synthetic Hidden Markov Model (HMM) tasks to test if trans…
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South Korea declines Trump's call to join Hormuz Strait mission
South Korea has declined Donald Trump's request to send naval forces to the Strait of Hormuz following a ship fire. Officials indicated that Seoul would require a UN mandate and a global coalition before participating i…
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Researchers develop MDP and POMDP for error mitigation in digital twins
Researchers have developed a new framework for mitigating error propagation in modular digital twins by treating it as a sequential decision-making problem. They formulated this using a Markov Decision Process (MDP) and…