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Kalman Filtering on Cell Complexes

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arXiv:2605. 15955v1 Announce Type: cross Abstract: Inferring latent dynamics from multivariate time-series defined over topological cell complexes is crucial for capturing the complex, higher-order interactions inherent in real-world systems such as in water, sensor, and transportation networks.

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Authors: Chengen Liu, Rohan Money, Ting Gao, Mohammad Sabbaqi, Baltasar Beferull-Lozano, Elvin Isufi
Released: 2026-05-18 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Kalman Filtering on Cell Complexes overlaps with clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)", clean result "The marker is a representational handle, not a behavioural one — sharing it between a villain persona and the assistant transfers no misalignment (HIGH confidence)", experiment "Follow-up to #354: cascading chunk-binding — does A→B, B→C, C→D propagate the full chain on a recipient trained only to emit A?". Matching terms: under, line, rate, full, model. Source: arxiv stat.ML (Machine Learning).
arXiv: 2605.15955

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