Cover Image

Finite-Width Neural Tangent Kernels from Feynman Diagrams

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Guillen, Max, Misof, Philipp, Gerken, Jan E.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning High Energy Physics - Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Criticality and Saturation in Orthogonal Neural Networks
by: Guillen, Max, et al.
Published: (2026)

Equivariant Neural Tangent Kernels
by: Misof, Philipp, et al.
Published: (2024)

Feynman Diagrams from Conformal Integrals
by: Prabhu, Siddharth G.
Published: (2024)

Learning to Unscramble Feynman Loop Integrals with SAILIR
by: Shih, David
Published: (2026)

Refining Integration-by-Parts Reduction of Feynman Integrals with Machine Learning
by: von Hippel, Matt, et al.
Published: (2025)

Strings from Feynman Diagrams
by: Gopakumar, Rajesh, et al.
Published: (2024)

Trivalent Feynman Diagrams as a Flag
by: Yang, Lili
Published: (2024)

Uncovering Singularities in Feynman Integrals via Machine Learning
by: Liu, Yuanche, et al.
Published: (2025)

Finite Integrals from Feynman Polytopes
by: de la Cruz, Leonardo, et al.
Published: (2024)

Planar Matrices and Arrays of Feynman Diagrams
by: Cachazo, Freddy, et al.
Published: (2019)

Position Space Equations for Banana Feynman Diagrams
by: Mishnyakov, Victor, et al.
Published: (2023)

Collective Kernel EFT for Pre-activation ResNets
by: Kawase, Hidetoshi, et al.
Published: (2026)

A Systematic Approach to Finite Multiloop Feynman Integrals
by: Dhani, Prasanna K., et al.
Published: (2026)

A Procedure g5anchor to Anchor $γ_5$ in Feynman Diagrams for the Standard Model
by: Chen, Long
Published: (2024)

Planar Matrices and Arrays of Feynman Diagrams: Poles for Higher $k$
by: Guevara, Alfredo, et al.
Published: (2020)

Les Houches Lectures on Deep Learning at Large & Infinite Width
by: Bahri, Yasaman, et al.
Published: (2023)

The Heat Kernel in Riemann Normal Coordinates and Multiloop Feynman Graphs in Curved Spacetime
by: Carneiro, Igor, et al.
Published: (2024)

Conformal Fields from Neural Networks
by: Halverson, James, et al.
Published: (2024)

Numerators in Parametric Representations of Feynman Diagrams
by: Bellon, Marc P.
Published: (2022)

Understanding Diffusion Models by Feynman's Path Integral
by: Hirono, Yuji, et al.
Published: (2024)

Rediscovery of Numerical Lüscher's Formula from the Neural Network
by: Lu, Yu, et al.
Published: (2022)

Tessellation Groups, Harmonic Analysis on Non-compact Symmetric Spaces and the Heat Kernel in view of Cartan Convolutional Neural Networks
by: Fré, Pietro, et al.
Published: (2025)

GUD: Generation with Unified Diffusion
by: Gerdes, Mathis, et al.
Published: (2024)

Learning S-Matrix Phases with Neural Operators
by: Niarchos, V., et al.
Published: (2024)

Neural Network Learning and Quantum Gravity
by: Lanza, Stefano
Published: (2024)

Conformal Defects in Neural Network Field Theories
by: Capuozzo, Pietro, et al.
Published: (2025)

Virasoro Symmetry in Neural Network Field Theories
by: Robinson, Brandon
Published: (2025)

Fermions and Supersymmetry in Neural Network Field Theories
by: Frank, Samuel, et al.
Published: (2025)

Feynman Diagrams
by: Weinzierl, Stefan
Published: (2025)

Detecting Homeomorphic 3-manifolds via Graph Neural Networks
by: Lawrie, Craig, et al.
Published: (2024)

The Modification of Feynman Diagrams in Curved Space-Time
by: Li, Benliang
Published: (2024)

String Theory from Infinite Width Neural Networks
by: Frank, Samuel, et al.
Published: (2026)

Navigation through Non-Compact Symmetric Spaces: a mathematical perspective on Cartan Neural Networks
by: Fré, Pietro Giuseppe, et al.
Published: (2025)

Recent developments from Feynman integrals
by: Marzucca, Robin, et al.
Published: (2023)

Learning the S-matrix from data: Rediscovering gravity from gauge theory via symbolic regression
by: Moynihan, Nathan
Published: (2026)

Uncertainty Quantification From Scaling Laws in Deep Neural Networks
by: Elsharkawy, Ibrahim, et al.
Published: (2025)

Unregulated Divergences of Feynman Integrals
by: Chen, Wen
Published: (2024)

Seedless Reduction of Feynman Integrals
by: de la Cruz, Leonardo, et al.
Published: (2026)

Feynman integrals and Fox functions
by: Passarino, Giampiero
Published: (2024)

Reinforcement learning-based statistical search strategy for an axion model from flavor
by: Nishimura, Satsuki, et al.
Published: (2024)