Four self-stigma personas identified via LPA on 1,174 Reddit users; persona-conditioned LLMs achieve targeted shifts but experts prefer generic empathy baselines.
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A tutorial on hidden Markov models and selected applications in speech recognition
14 Pith papers cite this work, alongside 15,017 external citations. Polarity classification is still indexing.
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Tropical Viterbi tubes are defined as superlevel sets of complete-data log-scores around the Viterbi optimum in HMMs, computed exactly via max-plus recursions and illustrated on bat-tracking data.
The authors introduce Time to Transition (TtT) extracted from cross-maturity greenium differences and develop tractable deadline-constrained and regime-switching diffusion models with exact likelihoods and asymptotic identification results for inference.
ExplainFuzz generates coherent, constraint-satisfying test inputs via grammar-compiled probabilistic circuits, raising bug-trigger rates from 35% to 63% in SQL and 10% to 100% in XML over mutational fuzzing.
QATS is a new polylog-time approximate decoding procedure for HMMs that builds admissible state sequences by locally maximizing likelihoods over paths with at most three segments via adaptive ternary segmentation and cumulative sum storage.
An HSMM integrated with discrete-time survival analysis is applied to four years of Shanghai metro smart card data to identify five mobility states, directional transitions, and state-dependent exit/re-entry hazards.
Derives closed-form expressions for the score and observed Fisher information matrix in a noisy Gaussian random walk HMM via Oakes' identity and forward-backward algorithm.
Rank correlation (Kendall tau) of price forecasts, not mean absolute error, determines intraday dispatch value for multi-market battery storage, with tau above 0.85-0.95 capturing 97-100% of perfect-foresight revenue.
Analysis of 1990-2022 LIS papers via automatic extraction of method entities identifies data resources as the central driver of methodological change exhibiting a cyclical emergence-stability pattern.
libhmm is a C++20 library implementing correct MLE emission M-steps for 16 distributions in HMMs via Baum-Welch, with log-space forward-backward/Viterbi and SIMD acceleration.
CircuITS is a probabilistic-circuit architecture that structurally guarantees valid joint distributions for irregular multivariate time series while outperforming baselines on joint and marginal density estimation across four real-world datasets.
CRANE applies a Hidden Markov Model to correct errors in raw nanopore signals and reports consistent accuracy gains for downstream raw-signal analysis tools with low added compute cost.
Quantum LSTM and quantum reservoir computing match classical baselines in univariate financial forecasting and modestly outperform them in multivariate cases with correlated inputs when using suitable lag structures and amplitude encoding.
A Hidden Markov Model on STFT-derived spectral features from welding current signals identifies three temporally coherent arc regimes: transient, stable, and extinction.
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Self-Stigma Is Not a Monolith, but Generic Empathy Is: Persona-Conditioned LLM Support for People Who Use Drugs
Four self-stigma personas identified via LPA on 1,174 Reddit users; persona-conditioned LLMs achieve targeted shifts but experts prefer generic empathy baselines.
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Tropical Viterbi Tubes for Decoding Uncertainty in Hidden Markov Models
Tropical Viterbi tubes are defined as superlevel sets of complete-data log-scores around the Viterbi optimum in HMMs, computed exactly via max-plus recursions and illustrated on bat-tracking data.
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Market-implied time to transition to a low-carbon economy: a stochastic modelling and inference framework
The authors introduce Time to Transition (TtT) extracted from cross-maturity greenium differences and develop tractable deadline-constrained and regime-switching diffusion models with exact likelihoods and asymptotic identification results for inference.
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ExplainFuzz: Explainable and Constraint-Conditioned Test Generation with Probabilistic Circuits
ExplainFuzz generates coherent, constraint-satisfying test inputs via grammar-compiled probabilistic circuits, raising bug-trigger rates from 35% to 63% in SQL and 10% to 100% in XML over mutational fuzzing.
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Quick Adaptive Ternary Segmentation: An Efficient Decoding Procedure For Hidden Markov Models
QATS is a new polylog-time approximate decoding procedure for HMMs that builds admissible state sequences by locally maximizing likelihoods over paths with at most three segments via adaptive ternary segmentation and cumulative sum storage.
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Understanding Long-Term Dynamics of Individual Metro Usage: A Hidden Semi-Markov State Framework with Survival Analysis
An HSMM integrated with discrete-time survival analysis is applied to four years of Shanghai metro smart card data to identify five mobility states, directional transitions, and state-dependent exit/re-entry hazards.
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Observed Fisher Information in hidden Markov models - Application to a noisy Gaussian random walk
Derives closed-form expressions for the score and observed Fisher information matrix in a noisy Gaussian random walk HMM via Oakes' identity and forward-backward algorithm.
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When Forecast Accuracy Fails: Rank Correlation and Decision Quality in Multi-Market Battery Storage Optimization
Rank correlation (Kendall tau) of price forecasts, not mean absolute error, determines intraday dispatch value for multi-market battery storage, with tau above 0.85-0.95 capturing 97-100% of perfect-foresight revenue.
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Data-Driven Evolution of Library and Information Science Research Methods (1990-2022): A Perspective Based on Fine-grained Method Entities
Analysis of 1990-2022 LIS papers via automatic extraction of method entities identifies data resources as the central driver of methodological change exhibiting a cyclical emergence-stability pattern.
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libhmm: A Modern C++20 Library for Hidden Markov Models with Correct MLE Emission M-Steps
libhmm is a C++20 library implementing correct MLE emission M-steps for 16 distributions in HMMs via Baum-Welch, with log-space forward-backward/Viterbi and SIMD acceleration.
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Probabilistic Circuits for Irregular Multivariate Time Series Forecasting
CircuITS is a probabilistic-circuit architecture that structurally guarantees valid joint distributions for irregular multivariate time series while outperforming baselines on joint and marginal density estimation across four real-world datasets.
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CRANE: Correcting Errors in Raw Nanopore Signals Using Hidden Markov Models
CRANE applies a Hidden Markov Model to correct errors in raw nanopore signals and reports consistent accuracy gains for downstream raw-signal analysis tools with low added compute cost.
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Learning Temporal Patterns in Financial Time Series: A Comparative Study of Quantum LSTM and Quantum Reservoir Computing
Quantum LSTM and quantum reservoir computing match classical baselines in univariate financial forecasting and modestly outperform them in multivariate cases with correlated inputs when using suitable lag structures and amplitude encoding.
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A Hidden Markov Framework for Physically Interpretable Arc Stability Dynamics in Welding Systems
A Hidden Markov Model on STFT-derived spectral features from welding current signals identifies three temporally coherent arc regimes: transient, stable, and extinction.