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NeurIPS 2026SpotlightNational University of SingaporeDeep learning theory

Point-to-Manifold Geometry: Flexibly Overcoming the Curse of Dimensionality in Neural Computational Units

Rohan Ghosh, Mehul Motani

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

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NeurIPS 2026Indian Institute of Technology DIndian Institute of Technology RDeep learning theory

Statistical Mixing Guarantees for Contractive Echo State Networks

Pradeep Singh, Balasubramanian Raman

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

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NeurIPS 2026Indian Institute of Technology DIndian Institute of Information Indian Institute of Technology RDeep learning theory

Dimension Bounds for Contractive Reservoir Computing from Input Entropy

Pradeep Singh, Kishore Babu Nampalle, Balasubramanian Raman

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026HarvardDeep learning theory

Temporal Smoothness Constraints on Efficient Neurobiological Codes Imply Temporal Specialization

John Vastola, Samuel J Gershman

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026The University of Hong KongThe Univeristy of HongkongDeep learning theory

Looped Transformers with Layer Normalization Provably Learn the Power Method

Lyumin Wu, Chenyang Zhang, Yuan Cao

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U QueenslandU MelbourneU California, BerkeleyUC BerkeleyDeep learning theory

Why Heavy-Tailed Weights Predict Model Quality

Joseph Wilson, Chris van der Heide, Liam Hodgkinson, Zhichao Wang and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026PekingKuaishou- 快手科技Kling, KuaishouKuaishou TechnologyDeep learning theory

On the Instability and Stabilization of Blockwise Muon

Yuanshi Liu, Weicheng Lin, Boyuan Jiang, Xin Tao and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U California, San DiegoU California, BerkeleyDeep learning theory

NTK Regression under dual power-law model: Deterministic Equivalents via SDE and PDE Methods

Collin Cranston, Zhichao Wang, Todd Kemp

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026State University of New York at U FloridaUniversity at Buffalo-SUNYState University of New York BufDeep learning theory

Elastic Representations via Hyperbolic Geometry

Arjun Ramesh Kaushik, Rudrasis Chakraborty, Nalini Ratha, Venu Govindaraju

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026The Hong Kong University of ScieThe Hong Kong University of ScieDeep learning theory

The Alternation Depth Principle for Neural Operator Design

Haoze Song, Zhilu Lai, Wei Wang

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

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NeurIPS 2026U MichiganMassachusetts Institute of TechnMassachusetts Institute of TechnDeep learning theory

Topological Invariance and Breakdown in Learning Dynamics

Yongyi Yang, Tomaso Poggio, Isaac Chuang, Liu Ziyin

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U California, Santa BarbaraJohns HopkinsDeep learning theory

Synaptic Strength Controls Trainability and Structural Stability in Rank-Deficient RNNs

Fatih Dinc, Edouard Ponnat, Henrik Weyer, Yanin Guerra and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026The Chinese University of Hong KThe Chinese University of Hong KDeep learning theory

Spectral Degeneration of Softmax Attention under Isotropic Score Geometry

Mengda Li, Jianfeng Yao

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

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NeurIPS 2026SpotlightU Electronic Science and TechnolDeep learning theory

Phase Kernel Lifts Capacity of Dense Associative Memory

Yifei Zhao, Ying Tang

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

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NeurIPS 2026B0Labs, N2TP TechnologyNanyang TechnologicalN2TPN2TP Technology Solutions JSCHanoi University of PharmacyDeep learning theory

Spectral Identifiability for World Models: Polynomial Projectors, Resolvent Stability, and a Krylov Bottleneck

Phan Quoc Hung Mai, Duc H Nguyen, Luong Doan, Ngoc Mai Vu and 4 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026HarvardDeep learning theory

The Cost of Symmetry: Universality and Hardness for Permutation-Invariant Neural Networks

Dashiell Bhattacharyya

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026MITCarnegie MellonDeep learning theory

Fast Approximate $\ell_p$ Chamfer Distance via Lopsided Embeddings and Structured JL

Ying Feng, David Woodruff

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Academia SinicaDeep learning theory

Compositional Generalization Certificates via the Van Kampen Theorem

Karen Sargsyan

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

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NeurIPS 2026OralIndependentZhejiangDeep learning theory

FLIP: Fast and Accurate Global Lipschitz Estimation for Large Feedforward Networks

Hongbo Chen, Zihao Ren

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

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NeurIPS 2026Hamburg University of TechnologyRuhr University Bochum, ELLIS UnRuhr University BochumTechnische Universität HamburgDeep learning theory

The Optimal Control Foundation of Early Exits – Turnpikes and ResNets

Jens Püttschneider, Simon Heilig, Asja Fischer, Timm Faulwasser

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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