MSE-optimal multi-step forecasters cannot match the marginal distribution of realizations under nonzero conditional uncertainty, creating a quantifiable accuracy-realism Pareto frontier across benchmarks.
Title resolution pending
8 Pith papers cite this work. Polarity classification is still indexing.
8
Pith papers citing it
citation-role summary
background 1
baseline 1
citation-polarity summary
years
2026 8representative citing papers
Dynamic Time Warping with a shared warping path across parameters aligns binary stellar tracks for accurate interpolation while preserving physical relationships such as the Stefan-Boltzmann law.
Decoder-only transformer generates mechanisms from VAE latents of target curves, reporting mean Chamfer distance 0.0132 on held-out tests while avoiding explicit dataset lookup.
A multi-branch β-VAE on tropical Pacific SST, OHC, and OLR fields yields a latent space that reconstructs data well and aligns with physical ENSO and longer-term coupled variability modes.
PREFAB applies preference learning grounded in the peak-end rule to let users annotate only key affective change segments while interpolating the rest, reducing workload and improving confidence in a 25-participant study.
MoVA introduces modular asymmetric dual projections to handle temporal misalignment and semantic asymmetry in long video-text alignment.
SAT-RTS introduces a pipeline that abstracts high-dimensional RTS sequences into discrete tactical labels and hierarchical visualizations to improve interpretability of AI micromanagement.
Nine care-trajectory clusters derived from Dynamic Time Warping and hierarchical clustering independently predict mortality in cancer patients and show an inverse link to baseline anxiety in high-utilization groups.
citing papers explorer
-
Expectations vs. Realities: The Cost of MSE-Optimal Forecasting Under Conditional Uncertainty
MSE-optimal multi-step forecasters cannot match the marginal distribution of realizations under nonzero conditional uncertainty, creating a quantifiable accuracy-realism Pareto frontier across benchmarks.