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2212.07892

Multimodal Teacher Forcing for Reconstructing Nonlinear Dynamical Systems

Manuel Brenner, Georgia Koppe, Daniel Durstewitz

correctmedium confidence
Category
Not specified
Journal tier
Strong Field
Processed
Sep 28, 2025, 12:56 AM

Audit review

The candidate solution derives exactly the same consistency loss and total MVAE-TF objective as the paper: starting from the MVAE negative ELBO (Eq. 5), instantiating the prior with timewise Gaussians centered at z_{1:K,t}, noting the t=1 term vanishes because z1 is initialized from \tilde z1, and arriving at L_cons in Eq. 8; then combining with the dendPLRNN likelihood to get L_total in Eq. 9 . The only minor notational mismatch is that the paper’s L_MVAE in Eq. 9 refers to the reconstruction plus entropy terms (first and third terms of Eq. 5), whereas the model first wrote L_MVAE as the full negative ELBO before replacing the prior term with L_cons; the final expression still matches the paper’s Eq. 9 .

Referee report (LaTeX)

\textbf{Recommendation:} minor revisions

\textbf{Journal Tier:} strong field

\textbf{Justification:}

The model’s derivation tracks the paper’s equations precisely and reaches the same objective, including the vanishing t=1 contribution and the resulting consistency loss. The only point needing clarification is the definition of L\_MVAE in the final decomposition to avoid possible double counting of the prior. Otherwise, the logic is coherent, standard Gaussian algebra is applied correctly, and the coupling between MVAE latents and the dendPLRNN prior is well justified.