Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains | Paper Citation Record

Observation 71426ec0-ba48-4e8d-907f-82c1269f2258 · inbound

NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction cites this paper.

NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T20:17:59.334507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8638acfd-0ce9-4798-a0d6-ab8f042a0f69 · inbound

Nomic Embed: Training a Reproducible Long Context Text Embedder cites this paper.

Nomic Embed: Training a Reproducible Long Context Text Embedder Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-21T14:56:19.204582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6af094b6-c79a-4267-b38d-435c13c8f340 · inbound

SPLIT: SE(3)-diffusion via Local Geometry-based Score Prediction for 3D Scene-to-Pose-Set Matching Problems cites this paper.

SPLIT: SE(3)-diffusion via Local Geometry-based Score Prediction for 3D Scene-to-Pose-Set Matching Problems Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-12T20:06:27.169438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fedc8d9-5287-4697-ac3d-eb1759351c04 · inbound

Confidence-Aware Deep Learning for Load Plan Adjustments in the Parcel Service Industry cites this paper.

Confidence-Aware Deep Learning for Load Plan Adjustments in the Parcel Service Industry Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T12:10:12.155712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7d45915-f5fa-4b7d-b06a-f7be8b55f07e · inbound

Diffusion models learn distributions generated by complex Langevin dynamics cites this paper.

Diffusion models learn distributions generated by complex Langevin dynamics Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-12T00:08:52.179916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6dc4b5b5-3a68-470e-83bc-e78f7d26ca85 · inbound

IRisPath: Enhancing Costmap for Off-Road Navigation with Robust IR-RGB Fusion for Improved Day and Night Traversability cites this paper.

IRisPath: Enhancing Costmap for Off-Road Navigation with Robust IR-RGB Fusion for Improved Day and Night Traversability Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T22:45:29.419223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 026544cf-3ed9-4462-a684-c793d2a891f3 · inbound

Is the neural tangent kernel of PINNs deep learning general partial differential equations always convergent ? cites this paper.

Is the neural tangent kernel of PINNs deep learning general partial differential equations always convergent ? Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T20:07:55.485433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd7814cb-370f-42bc-82fc-643a728e15f7 · inbound

Predicting Change, Not States: An Alternate Framework for Neural PDE Surrogates cites this paper.

Predicting Change, Not States: An Alternate Framework for Neural PDE Surrogates Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-11T13:31:12.192502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0adb4561-b981-4586-9495-2edb9dcf493d · inbound

NeuralSVG: An Implicit Representation for Text-to-Vector Generation cites this paper.

NeuralSVG: An Implicit Representation for Text-to-Vector Generation Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-10T21:45:55.026563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6d8e74b-5623-4cd1-85c8-45636e9068f9 · inbound

Optimization Landscapes Learned: Proxy Networks Boost Convergence in Physics-based Inverse Problems cites this paper.

Optimization Landscapes Learned: Proxy Networks Boost Convergence in Physics-based Inverse Problems Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-10T12:16:12.799090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c8107f1-62a6-4dc9-8272-5c8bd2e10932 · inbound

Meta-neural Topology Optimization: Knowledge Infusion with Meta-learning cites this paper.

Meta-neural Topology Optimization: Knowledge Infusion with Meta-learning Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-09T14:22:40.072386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6e000ff-8f4c-4b42-b7ef-d92ccc8ed119 · inbound

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings cites this paper.

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T12:15:20.834044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6a41620-317b-4339-aef1-cc14f6f5ef1e · inbound

Object Learning and Robust 3D Reconstruction cites this paper.

Object Learning and Robust 3D Reconstruction Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 189

Resolution: unresolved; no resolver link, observed 2026-08-16T11:12:33.773172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2b247f9-066f-45a2-91b9-76d66f8fe7b2 · inbound

QFGN: A Quantum Approach to High-Fidelity Implicit Neural Representations cites this paper.

QFGN: A Quantum Approach to High-Fidelity Implicit Neural Representations Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T10:08:28.857926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb371b2c-e9aa-43c6-846a-90f16c5b1dda · inbound

Transformer-Based Dual-Optical Attention Fusion Crowd Head Point Counting and Localization Network cites this paper.

Transformer-Based Dual-Optical Attention Fusion Crowd Head Point Counting and Localization Network Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T22:34:34.724912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0073fb32-6756-44d5-b2e9-a191a0df6796 · inbound

Hybrid Adaptive Modeling in Process Monitoring: Leveraging Sequence Encoders and Physics-Informed Neural Networks cites this paper.

Hybrid Adaptive Modeling in Process Monitoring: Leveraging Sequence Encoders and Physics-Informed Neural Networks Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:53.252576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a277a347-36e5-47f9-be80-13a51fe79f3b · inbound

BlastOFormer: Attention and Neural Operator Deep Learning Methods for Explosive Blast Prediction cites this paper.

BlastOFormer: Attention and Neural Operator Deep Learning Methods for Explosive Blast Prediction Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T13:58:19.451025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 492c8ec2-fb6d-4b53-bd00-d621cc37557a · inbound

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks cites this paper.

SPINN: Advancing Cosmological Simulations of Fuzzy Dark Matter with Physics Informed Neural Networks Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:59.200209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27c16d0e-8299-4644-922a-4a85167292ac · inbound

Theoretical Analysis of Positional Encodings in Transformer Models: Impact on Expressiveness and Generalization cites this paper.

Theoretical Analysis of Positional Encodings in Transformer Models: Impact on Expressiveness and Generalization Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T10:19:31.558026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50cc908e-a05e-494e-8d14-8c3db0d3697d · inbound

Low-Rank Augmented Implicit Neural Representation for Unsupervised High-Dimensional Quantitative MRI Reconstruction cites this paper.

Low-Rank Augmented Implicit Neural Representation for Unsupervised High-Dimensional Quantitative MRI Reconstruction Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T05:05:27.042285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3819ba53-f613-4b1f-b47b-32922abd182f · inbound

DiffPR: Diffusion-Based Phase Reconstruction via Frequency-Decoupled Learning cites this paper.

DiffPR: Diffusion-Based Phase Reconstruction via Frequency-Decoupled Learning Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T04:19:43.929738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52a74495-5cb7-49c5-8ed0-a4daa94e4d6e · inbound

FlatCAD: Fast Curvature Regularization of Neural SDFs for CAD Models cites this paper.

FlatCAD: Fast Curvature Regularization of Neural SDFs for CAD Models Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-15T19:28:02.158865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afa383e4-1c9d-4e65-9575-1c74f0135f40 · inbound

Efficient many-jet event generation with Flow Matching cites this paper.

Efficient many-jet event generation with Flow Matching Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-15T18:48:36.776891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d13167a-51c8-4ac2-bab7-87a4a1fd9307 · inbound

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure cites this paper.

Operator-based machine learning framework for generalizable prediction of unsteady treatment dynamics in stormwater infrastructure Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T19:47:00.699993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65b59399-bfd1-4de3-9ae1-049c4f007271 · inbound

Physics-informed machine learning surrogate for scalable simulation of thermal histories during wire-arc directed energy deposition cites this paper.

Physics-informed machine learning surrogate for scalable simulation of thermal histories during wire-arc directed energy deposition Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T17:57:32.676173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8b3dec1-7e93-42f4-9184-a4dc0faad7e8 · inbound

ExtraGS: Geometric-Aware Trajectory Extrapolation with Uncertainty-Guided Generative Priors cites this paper.

ExtraGS: Geometric-Aware Trajectory Extrapolation with Uncertainty-Guided Generative Priors Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T17:53:40.735784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27eb93fe-cb7e-4b88-bd28-9b8fb2d5418d · inbound

Maybe you don't need a U-Net: convolutional feature upsampling for materials micrograph segmentation cites this paper.

Maybe you don't need a U-Net: convolutional feature upsampling for materials micrograph segmentation Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T16:44:21.081309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f05e8f5e-959c-40d4-ad73-66780fa66c2b · inbound

Continuously Tempered Diffusion Samplers cites this paper.

Continuously Tempered Diffusion Samplers Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T13:56:09.002911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dc5ad31-fce9-44a2-a98c-43ec4123a0ab · inbound

FEDONet : Fourier-Embedded DeepONet for Spectrally Accurate Operator Learning cites this paper.

FEDONet : Fourier-Embedded DeepONet for Spectrally Accurate Operator Learning Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-18T16:06:35.166950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4b25e770-833e-4ddf-823a-b3f1b27b40b7 · inbound

Combining complex Langevin dynamics with score-based and energy-based diffusion models cites this paper.

Combining complex Langevin dynamics with score-based and energy-based diffusion models Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-04T13:16:09.020210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 268c15df-a7ad-49cd-b6ac-45bda02129a7 · inbound

Spectral Embedding via Chebyshev Bases for Robust DeepONet Approximation cites this paper.

Spectral Embedding via Chebyshev Bases for Robust DeepONet Approximation Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-03T17:33:55.945911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4810f874-65eb-46e9-ba44-230566b251be · inbound

A universal vision transformer for fast calorimeter simulations cites this paper.

A universal vision transformer for fast calorimeter simulations Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T12:08:19.579957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c379969f-36c2-4d5d-9911-ccdab21c2050 · inbound

Gradient Networks for Universal Magnetic Modeling of Synchronous Machines cites this paper.

Gradient Networks for Universal Magnetic Modeling of Synchronous Machines Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T23:06:37.242148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84dcbeb8-3cfe-4890-9ce4-607a89b43b6e · inbound

Deep learning-based phase-field modelling of brittle fracture in anisotropic media cites this paper.

Deep learning-based phase-field modelling of brittle fracture in anisotropic media Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:15:11.938836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e6131349-930b-427f-81a9-e52b0880b1f0 · inbound

Learning 3D Hypersonic Flow with Physics-Enhanced Neural Fields: A Case Study on the Orion Reentry Capsule cites this paper.

Learning 3D Hypersonic Flow with Physics-Enhanced Neural Fields: A Case Study on the Orion Reentry Capsule Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 1845

Resolution: unresolved; no resolver link, observed 2026-08-02T17:47:09.277877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95af2e58-9127-4783-87d0-7abcc0de49e3 · inbound

Cell-induced densification and tether formation in fibrous extracellular matrices with biomimetic physics-informed neural networks cites this paper.

Cell-induced densification and tether formation in fibrous extracellular matrices with biomimetic physics-informed neural networks Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T00:33:30.278709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7b7def32-1e14-43ff-b386-78cf9041c85b · inbound

Monte Carlo Event Generation with Continuous Normalizing Flows cites this paper.

Monte Carlo Event Generation with Continuous Normalizing Flows Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:58:04.231144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 286ab6ab-59e2-4e13-81df-717c4e5f0a44 · inbound

AE-ViT: Stable Long-Horizon Parametric Partial Differential Equations Modeling cites this paper.

AE-ViT: Stable Long-Horizon Parametric Partial Differential Equations Modeling Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-10T23:05:48.946119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b52de1d5-3207-4713-9051-77708b8320fc · inbound

A Deep Ritz Method for High-Dimensional Steady States of the Cahn-Hilliard Equation cites this paper.

A Deep Ritz Method for High-Dimensional Steady States of the Cahn-Hilliard Equation Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:50:21.381148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 46104e5e-5299-40af-9432-9762ebf385c2 · inbound

When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions cites this paper.

When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 66

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T21:06:14.634335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1310b24e-e26d-45af-a7b5-4458c44815bb · inbound

Physics informed operator learning of parameter dependent spectra cites this paper.

Physics informed operator learning of parameter dependent spectra Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:26:14.648751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2a66ae0b-42b3-4c20-8a2e-6d95682479ab · inbound

From Characterization To Construction: Generative Quantum Circuit Synthesis from Gate Set Tomography Data cites this paper.

From Characterization To Construction: Generative Quantum Circuit Synthesis from Gate Set Tomography Data Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:51:05.919938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 94227d5f-a0f5-4f5f-9a60-4a8e5ca434ad · inbound

MoMo: Conditioned Contrastive Representation Learning for Preference-Modulated Planning cites this paper.

MoMo: Conditioned Contrastive Representation Learning for Preference-Modulated Planning Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:51:45.393216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1cfaa5c6-36dd-4e3b-bc27-b63659948518 · inbound

MoMo: Conditioned Contrastive Representation Learning for Preference-Modulated Planning cites this paper.

MoMo: Conditioned Contrastive Representation Learning for Preference-Modulated Planning Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-15T06:09:50.072838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f6ada443-250b-47ea-8a35-b6832c0b3051 · inbound

LiFT: Lifted Inter-slice Feature Trajectories for 3D Image Generation from 2D Generators cites this paper.

LiFT: Lifted Inter-slice Feature Trajectories for 3D Image Generation from 2D Generators Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-20T10:58:13.923016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7b02529e-fc38-4827-be57-7fe37c10ec8c · inbound

RoPeSLR: 3D RoPE-driven Sparse-LowRank Attention for Efficient Diffusion Transformers cites this paper.

RoPeSLR: 3D RoPE-driven Sparse-LowRank Attention for Efficient Diffusion Transformers Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:59:41.183966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 676b36f0-999e-4728-8ac7-3ecc80638f77 · inbound

IV-Net: A neural network for elliptic PDEs with random and highly varying coefficients cites this paper.

IV-Net: A neural network for elliptic PDEs with random and highly varying coefficients Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-06-29T23:54:03.181998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8fe755c8-6ec6-4900-8992-4a23c8478b8d · inbound

Machine Learning-based Separation of the He I 10830{\AA} Chromospheric Signal: Quantitative Analysis of Chromosphere-Corona Intensity in the Quiet Sun cites this paper.

Machine Learning-based Separation of the He I 10830{\AA} Chromospheric Signal: Quantitative Analysis of Chromosphere-Corona Intensity in the Quiet Sun Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T20:53:57.461674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 840988bb-5ce6-4b9e-a84a-b4af1100ec3f · inbound

Flow Matching for Convective-Scale Precipitation Downscaling cites this paper.

Flow Matching for Convective-Scale Precipitation Downscaling Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:12:34.893025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 598196bb-193a-482a-8bee-722e86880a7b · inbound

Multi-Resolution Tactile Imitation Learning for Contact-Rich Robotic Manipulation cites this paper.

Multi-Resolution Tactile Imitation Learning for Contact-Rich Robotic Manipulation Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-07-02T13:46:59.674247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6dda2e37-0855-4f30-a0a9-3d6acf65ac47 · inbound

General-Purpose Nonlinear Function Approximation via Linear Integrated Photonics cites this paper.

General-Purpose Nonlinear Function Approximation via Linear Integrated Photonics Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T12:39:50.013570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7be01ce3-32cf-48b1-bd11-df37027ed60e · inbound

One Generator, Any Process: LLM-Conditioning for the LHC cites this paper.

One Generator, Any Process: LLM-Conditioning for the LHC Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 278

Resolution: verified exact; arxiv_id, observed 2026-07-04T11:39:46.434724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 484b785f-92b2-425a-8d8f-6d141d94ff3d · inbound

One Generator, Any Process: LLM-Conditioning for the LHC cites this paper.

One Generator, Any Process: LLM-Conditioning for the LHC Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 282

Resolution: verified exact; arxiv_id, observed 2026-06-30T10:14:36.072273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 76de2aa2-1185-4316-b135-4f111e9d4062 · inbound

Sampling the Schwinger Model with Gauge-Equivariant Diffusion cites this paper.

Sampling the Schwinger Model with Gauge-Equivariant Diffusion Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-01T18:55:59.293787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 15843b6b-281c-4302-8faf-49087cc3047e · inbound

Confidence-feedback-weighted graph matching network: online-offline laser-induced damage site matching under complex interference cites this paper.

Confidence-feedback-weighted graph matching network: online-offline laser-induced damage site matching under complex interference Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 43

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T08:14:25.564771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 92a7b196-1e0f-4af2-bcca-50d6653d41bf · inbound

Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding cites this paper.

Self-Supervised Implicit CEST Reconstruction via Physics-Informed Lorentz Encoding Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 9

Resolution: metadata mismatch; local_arxiv, observed 2026-07-08T15:55:04.535682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ca106430-2b83-4a3c-818e-d63155562d44 · inbound

LUMI: Tokenizer-Agnostic LLM-Based Lossless Image Compression cites this paper.

LUMI: Tokenizer-Agnostic LLM-Based Lossless Image Compression Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 28

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T11:07:01.952991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 86909be1-1f37-40b5-b794-11a14fa2b093 · inbound

Performance of Krotov, PRONTO and PINN for optimal control of quantum gates cites this paper.

Performance of Krotov, PRONTO and PINN for optimal control of quantum gates Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 37

Resolution: unresolved; no resolver link, observed 2026-07-31T23:55:43.798083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 567c592d-e321-41fe-b4eb-c8e9421f0cdb · inbound

Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms cites this paper.

Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 72

Resolution: unresolved; no resolver link, observed 2026-07-31T04:58:16.876298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8ea98f9-ca2f-464a-9eba-1b562cafb8d9 · inbound

Cosmo-SPINN: Fuzzy Dark Matter Simulations with Physics-Informed Generative Networks cites this paper.

Cosmo-SPINN: Fuzzy Dark Matter Simulations with Physics-Informed Generative Networks Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 51

Resolution: unresolved; no resolver link, observed 2026-07-31T02:27:16.914894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 575fbb20-04dc-42d9-9e6f-2d413c7bf9c0 · inbound

Few-shot Deep Learning for Phase-Amplitude Aberration Correction in Transcranial Focused Ultrasound cites this paper.

Few-shot Deep Learning for Phase-Amplitude Aberration Correction in Transcranial Focused Ultrasound Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T12:14:43.238693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c563f81-68f2-46a3-9065-546d148a5d9e · inbound

An Artificial-Compressibility Physics-Informed Neural Network for the Unsteady Incompressible Navier--Stokes Equations cites this paper.

An Artificial-Compressibility Physics-Informed Neural Network for the Unsteady Incompressible Navier--Stokes Equations Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T14:47:09.097985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e764fb4-8885-4b8e-af08-772c097dd48b · inbound

A Hybrid Neural-Microfacet BRDF Model for Real-Time Rendering cites this paper.

A Hybrid Neural-Microfacet BRDF Model for Real-Time Rendering Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains

Reference 108

Resolution: unresolved; no resolver link, observed 2026-08-11T14:16:03.961000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers