Neural network-parameterized regression splines enable joint optimization of forecast quality and stability in distribution-free probabilistic time series models by penalizing dissimilarities from forecast updates.
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4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
Derives a closed-form Shapley value for the squared robust Interval-Mahalanobis distance to explain variable contributions to outlyingness in interval-valued data.
Traits Run Deeper proposes MFR, TSMF asymmetric fusion, and DCPR modules to improve multimodal personality assessment, claiming 25% MSE reduction and first place on AVI Challenge 2026.
A factorized generative Markov model is proposed for distributed computing systems to enable tractable simulation, inference, and policy learning, shown in a collaborative AI inference case study.
citing papers explorer
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Stabilizing distribution-free probabilistic forecasts
Neural network-parameterized regression splines enable joint optimization of forecast quality and stability in distribution-free probabilistic time series models by penalizing dissimilarities from forecast updates.
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Explainable Outlier Detection for Interval-valued Data
Derives a closed-form Shapley value for the squared robust Interval-Mahalanobis distance to explain variable contributions to outlyingness in interval-valued data.
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Traits Run Deeper: Trait-Specific Asymmetric Fusion for Personality Assessment
Traits Run Deeper proposes MFR, TSMF asymmetric fusion, and DCPR modules to improve multimodal personality assessment, claiming 25% MSE reduction and first place on AVI Challenge 2026.
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Brief Announcement: Generative Markov Model for Distributed Computing Systems
A factorized generative Markov model is proposed for distributed computing systems to enable tractable simulation, inference, and policy learning, shown in a collaborative AI inference case study.