INDEQS is a graph-informed NCDE variant that separates inner hidden-state mixing from outer vector-field mixing and reports lower MAE than uninformed NCDEs on synthetic advection data and real river/traffic tasks when the graph is known.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
A computational MSV model built from short-video multimodal features positively predicts sensory engagement but shows an inverted-U relationship with behavioral engagement, validated on large unseen platform datasets.
citing papers explorer
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INDEQS: Informed Neural controlled Differential EQuationS
INDEQS is a graph-informed NCDE variant that separates inner hidden-state mixing from outer vector-field mixing and reports lower MAE than uninformed NCDEs on synthetic advection data and real river/traffic tasks when the graph is known.
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A Computational Model of Message Sensation Value in Short Video Multimodal Features that Predicts Sensory and Behavioral Engagement
A computational MSV model built from short-video multimodal features positively predicts sensory engagement but shows an inverted-U relationship with behavioral engagement, validated on large unseen platform datasets.