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Computation-Aware Kalman Filtering with Model Selection for Neural Dynamics

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arXiv:2606. 01468v1 Announce Type: new Abstract: Due to their explicit priors and ability to model uncertainty, Bayesian methods have played a major role in dynamical latent variable modeling of single-cell neural recordings.

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Authors: JR Huml, Jonathan Wenger, John P. Cunningham
Released: 2026-06-02 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because Computation-Aware Kalman Filtering with Model Selection for Neural Dynamics overlaps with experiment "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)". Matching terms: model. Source: arxiv stat.ML (Machine Learning).
arXiv: 2606.01468

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