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NeurIPS 2026SpotlightU PennsylvaniaSakana AINortheasternHarvardDeep learning theory

Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves

A Hilbert bundle convolutional framework defines HilbNets for infinite-dimensional manifold signals, proving discrete versions converge to continuous architectures and transfer across samplings.

Kartik Tandon, Julian J Gould, Tanishq Bhatia, Francesca Dominici and 2 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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8/20 AI panelreviewers recommend it

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AI panel: 8 of 20 reviewers recommend it
lenient 3/5
medium 3/10
strict 2/5
83%Must read
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NeurIPS 2026Sakana AIRepresentation & contrastive learning

Augmented Lagrangian Predictive Coding

Augmented Lagrangian Predictive Coding aligns local weight updates with backpropagation via per-layer Lagrange multipliers, matching backpropagation performance in deep narrow networks with ballistic credit propagation.

Jeffrey Seely, Julian J Gould

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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13/20 AI panelreviewers recommend it

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AI panel: 13 of 20 reviewers recommend it
lenient 3/5
medium 7/10
strict 3/5
76%Highly rated
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NeurIPS 2026SpotlightNew YorkBasisSakana AI3D generation

Dream-Cubed: Controllable Generative Modeling in Minecraft by Training on Billions of Cubes

Dream-Cubed introduces a billion-scale Minecraft voxel dataset and diffusion models that generate interactive 3D worlds directly from block tokens with inpainting and outpainting support.

Tim Merino, Sam Earle, Ryunosuke Iwai, Julian Togelius and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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10/20 AI panelreviewers recommend it

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AI panel: 10 of 20 reviewers recommend it
lenient 5/5
medium 3/10
strict 2/5