Cover Image

The Propagation Field: A Geometric Substrate Theory of Deep Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Gu, Xingrui
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Uncertainty-Gated Generative Modeling
by: Gu, Xingrui, et al.
Published: (2026)

Conceptual Belief-Informed Reinforcement Learning
by: Gu, Xingrui, et al.
Published: (2024)

DeepVekua: Geometric-Spectral Representation Learning for Physics-Informed Fields
by: Khasia, Vladimer
Published: (2025)

Learning in Deep Factor Graphs with Gaussian Belief Propagation
by: Nabarro, Seth, et al.
Published: (2023)

A Geometric Modeling of Occam's Razor in Deep Learning
by: Sun, Ke, et al.
Published: (2019)

Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration
by: Zhao, Heyang, et al.
Published: (2025)

A Unified Geometric Field Theory Framework for Transformers: From Manifold Embeddings to Kernel Modulation
by: Shi, Xianshuai, et al.
Published: (2025)

DeepSPoC: A Deep Learning-Based PDE Solver Governed by Sequential Propagation of Chaos
by: Du, Kai, et al.
Published: (2024)

Rhomboid Tiling for Geometric Graph Deep Learning
by: Zhang, Yipeng, et al.
Published: (2025)

The Role of Fibration Symmetries in Geometric Deep Learning
by: Velarde, Osvaldo, et al.
Published: (2024)

A Theory of Generalization in Deep Learning
by: Litman, Elon, et al.
Published: (2026)

The Loss Kernel: A Geometric Probe for Deep Learning Interpretability
by: Adam, Maxwell, et al.
Published: (2025)

Applications of Statistical Field Theory in Deep Learning
by: Ringel, Zohar, et al.
Published: (2025)

Advancing Analytic Class-Incremental Learning through Vision-Language Calibration
by: Zhao, Binyu, et al.
Published: (2026)

Mathematical Foundations of Geometric Deep Learning
by: Borde, Haitz Sáez de Ocáriz, et al.
Published: (2025)

There Will Be a Scientific Theory of Deep Learning
by: Simon, Jamie, et al.
Published: (2026)

Rethinking Deep Learning: Propagating Information in Neural Networks without Backpropagation and Statistical Optimization
by: Itoh, Kei
Published: (2024)

Do You Trust the Process?: Modeling Institutional Trust for Community Adoption of Reinforcement Learning Policies
by: Balepur, Naina, et al.
Published: (2025)

Spectral Convolution on Orbifolds for Geometric Deep Learning
by: Mangliers, Tim, et al.
Published: (2026)

On the Completeness of Invariant Geometric Deep Learning Models
by: Li, Zian, et al.
Published: (2024)

Is Distance Matrix Enough for Geometric Deep Learning?
by: Li, Zian, et al.
Published: (2023)

Geometric Deep Learning for Computer-Aided Design: A Survey
by: Heidari, Negar, et al.
Published: (2024)

Metric-Aware PCA as a Linear Instance of Geometric Deep Learning
by: Leznik, Michael
Published: (2026)

Critical Organization of Deep Neural Networks, and p-Adic Statistical Field Theories
by: Zúñiga-Galindo, W. A.
Published: (2026)

Geometric Dynamics of Signal Propagation Predict Trainability of Transformers
by: Cowsik, Aditya, et al.
Published: (2024)

Learning Hemodynamic Scalar Fields on Coronary Artery Meshes: A Benchmark of Geometric Deep Learning Models
by: Nannini, Guido, et al.
Published: (2025)

A Geometrically-Grounded Drive for MDL-Based Optimization in Deep Learning
by: Lei, Ming, et al.
Published: (2026)

Efficient Numerical Wave Propagation Enhanced By An End-to-End Deep Learning Model
by: Kaiser, Luis, et al.
Published: (2024)

FM-IRL: Flow-Matching for Reward Modeling and Policy Regularization in Reinforcement Learning
by: Wan, Zhenglin, et al.
Published: (2025)

Geometric Analysis of Unconstrained Feature Models with $d=K$
by: Shen, Yi, et al.
Published: (2024)

Artificial Neural Network and Deep Learning: Fundamentals and Theory
by: Hammad, M. M.
Published: (2024)

A Geometric Graph-Based Deep Learning Model for Drug-Target Affinity Prediction
by: Rana, Md Masud, et al.
Published: (2025)

Lightweight Geometric Deep Learning for Molecular Modelling in Catalyst Discovery
by: Geitner, Patrick
Published: (2024)

A Quadratic Synchronization Rule for Distributed Deep Learning
by: Gu, Xinran, et al.
Published: (2023)

Revisiting Deep Information Propagation: Fractal Frontier and Finite-size Effects
by: D'Inverno, Giuseppe Alessio, et al.
Published: (2025)

Exploring and Improving Initialization for Deep Graph Neural Networks: A Signal Propagation Perspective
by: Wang, Senmiao, et al.
Published: (2025)

Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble
by: Nitanda, Atsushi, et al.
Published: (2025)

Reconstructing Historical Climate Fields With Deep Learning
by: Bochow, Nils, et al.
Published: (2023)

SPD Learn: A Geometric Deep Learning Python Library for Neural Decoding Through Trivialization
by: Aristimunha, Bruno, et al.
Published: (2026)

Outdoor Environment Reconstruction with Deep Learning on Radio Propagation Paths
by: Khachatrian, Hrant, et al.
Published: (2024)