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Source: paper_references, paper_reference_links, observed 2026-08-07T04:19:45.941582Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 100 of 122 outbound references and 4 inbound Pith citation observations for arXiv:2506.10973.
A citation records a reference. It does not transfer a finding from one paper to another.
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Source: paper_references, paper_reference_links, observed 2026-08-07T04:19:45.941582Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-29T01:49:08.216819Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T00:07:27.763104Z
100 of 122 outbound references displayed
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Observation 00dd4194-410f-4427-94a8-3762b4fdd2ca · outbound
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Graph Neural Operators for Classification of Spatial Transcriptomics Data
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Scalable Second Order Optimization for Deep Learning
Reference 2
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Neural operators for accelerating scientific simulations and design
Reference 3
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Neural Machine Translation by Jointly Learning to Align and Translate
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Model reduction and neural networks for parametric PDEs
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Spherical Fourier neural operators: learning stable dynamics on the sphere
Reference 7
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning A Mathematical Guide to Operator Learning
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Lie point symmetry data augmentation for neural PDE solvers
Reference 9
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Message Passing Neural PDE Solvers
Reference 10
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Observation 18e57f7b-5bb5-4f61-aa7b-9cac3a344ace · outbound
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Continuum attention for neural operators
Reference 12
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning LNO: Laplace Neural Operator for Solving Differential Equations
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Choose a transformer: Fourier or Galerkin
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Neural operator surrogate models of plasma edge simulations: feasibility and data efficiency
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Fourier Neural Operator based surrogates for $CO_2$ storage in realistic geologies
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations
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Observation 64d9de40-2e1a-4e5a-80cb-d46c4f194e60 · outbound
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Equivariant neural operator learning with graphon convolution
Reference 18
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Rethinking Attention with Performers
Reference 19
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Fourier neural operator for fluid flow in small-shape 2D simulated porous media dataset
Reference 20
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Neural Operator Learning for Ultrasound Tomography Inversion
Reference 21
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Generic bounds on the approximation error for physics-informed (and) operator learning
Reference 22
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Nonlinear approximation
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Unresolved cited work
Reference 25
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Incremental Spatial and Spectral Learning of Neural Operators for Solving Large-Scale PDEs
Reference 26
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Understanding the difficulty of training deep feedforward neural networks
Reference 27
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Plasma surrogate modelling using fourier neural operators
Reference 29
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Observation 919b661d-c03b-4f7c-b2ee-7816d9aa21f7 · outbound
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Theory-to-Practice Gap for Neural Networks and Neural Operators
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers
Reference 31
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Multiwavelet-based operator learning for differential equations
Reference 32
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Towards Multi-spatiotemporal-scale Generalized PDE Modeling
Reference 33
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning GNOT : A general neural operator transformer for operator learning
Reference 34
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning DPOT : Auto-regressive denoising operator transformer for large-scale PDE pre-training
Reference 36
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
Reference 37
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Group Equivariant Fourier Neural Operators for Partial Differential Equations
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning A Unified Model for Compressed Sensing MRI Across Undersampling Patterns
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Perfception: Perception using radiance fields
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Jiang, Z
Reference 42
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Resolution-invariant image classification based on Fourier neural operators
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Adam: A Method for Stochastic Optimization
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Multi-Grid Tensorized Fourier Neural Operator for High-Resolution PDEs
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning A library for learning neural operators
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning FourCastNet : Accelerating global high-resolution weather forecasting using adaptive Fourier neural operators
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Artificial neural networks for solving ordinary and partial differential equations
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Operator learning with PCA-Net: upper and lower complexity bounds
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Error estimates for DeepONets : A deep learning framework in infinite dimensions
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Nonlocality and Nonlinearity Implies Universality in Operator Learning
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Discretization error of Fourier neural operators
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Layer normalization
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Fourier neural operator approach to large eddy simulation of three-dimensional turbulence
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Transformer for Partial Differential Equations' Operator Learning
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Neural Operator: Graph Kernel Network for Partial Differential Equations
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Multipole graph neural operator for parametric partial differential equations
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Physics-informed neural operator for learning partial differential equations
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Graph metanetworks for processing diverse neural architectures
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Lin, Julius Berner, Valentin Duruisseaux, David Pitt, Daniel Leibovici, Jean Kossaifi, Kamyar Azizzadenesheli, and Anima Anandkumar
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Tipping Point Forecasting in Non-Stationary Dynamics on Function Spaces
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Neural Operators with Localized Integral and Differential Kernels
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Effective Approaches to Attention-based Neural Machine Translation
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operators
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Fourier continuation for exact derivative computation in physics-informed neural operators
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning NeRF : Representing scenes as neural radiance fields for view synthesis
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning The well: a large-scale collection of diverse physics simulations for machine learning
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Pamela, N
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Generative Adversarial Neural Operators
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
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Reference 89
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Anoop Krishnan
Reference 90
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning An introduction to partial differential equations, volume 13
Reference 91
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning U-Net : Convolutional networks for biomedical image segmentation
Reference 92
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Reference 93
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Variational Autoencoding Neural Operators
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Reference 95
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Parallel physics-informed neural networks via domain decomposition
Reference 96
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning DGM : A deep learning algorithm for solving partial differential equations
Reference 97
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Implicit neural representations with periodic activation functions
Reference 98
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning RoFormer : Enhanced transformer with rotary position embedding
Reference 99
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Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Operator Learning: A Statistical Perspective
Reference 100
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Learning Neural Operator Surrogates for the Black Hole Accretion Code Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning
Reference 49
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Limits of Resolution Equivariance in Fourier Neural Operators Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning
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Evaluating Operators for Acoustic Wave Simulation Correction Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning
Reference 22
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Higher-Order Fourier Neural Operator: Explicit Mode Mixer for Nonlinear PDEs Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning
Reference 6
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