ITF inflates curvature in switching AL-RNNs by conditioning on one regime path while marginal likelihood reduces curvature with a missing-information correction for plausible switches, and evidence fine-tuning can degrade dynamical QoIs despite better held-out evidence.
The continuous-time Lorenz-63 dynamics are dz1 dt =σ(z2−z1), dz2 dt =z 1(ρ−z3)−z2, dz3 dt =z 1z2−βz3,(A45) with the standard chaotic parameter settingσ= 10, ρ= 28, and β= 8/3
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Teacher Forcing as Generalized Bayes: Optimization Geometry Mismatch in Switching Surrogates for Chaotic Dynamics
ITF inflates curvature in switching AL-RNNs by conditioning on one regime path while marginal likelihood reduces curvature with a missing-information correction for plausible switches, and evidence fine-tuning can degrade dynamical QoIs despite better held-out evidence.