ICLR 2026 - Submissions

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Submissions

Summary Statistics

Quantity AI Content Count Avg Rating
0-10% 1 (100%) 2.67
10-30% 0 (0%) N/A
30-50% 0 (0%) N/A
50-70% 0 (0%) N/A
70-90% 0 (0%) N/A
90-100% 0 (0%) N/A
Total 1 (100%) 2.67
Title Abstract Avg Rating Quantity AI Content Reviews Pangram Dashboard
Heteroscedastic Variational Bayesian Last Layers: Modeling Input-Dependent Noise in Sparse-Data Regression Bayesian Neural Networks (BNNs) have been extensively studied for uncertainty quantification. To train BNNs efficiently, Variational Bayesian Last Layer (VBLL) provides a sampling-free, deterministic ... 2.67 6% See Reviews View AI Dashboard
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