Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony | Paper Citation Record

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This paper cites Machine learning and the physical sciences,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Machine learning and the physical sciences,

Reference 1

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This paper cites Explainable machine learning for scientific insights and discoveries,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Explainable machine learning for scientific insights and discoveries,

Reference 2

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This paper cites Artificial intelligence: A powerful paradigm for scientific research,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Artificial intelligence: A powerful paradigm for scientific research,

Reference 3

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This paper cites Scientific discovery in the age of artificial intelligence,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Scientific discovery in the age of artificial intelligence,

Reference 4

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This paper cites Physics-informed machine learning,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Physics-informed machine learning,

Reference 5

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This paper cites Physics-informed machine learning: case studies for weather and climate modelling,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Physics-informed machine learning: case studies for weather and climate modelling,

Reference 6

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This paper cites Learning skillful medium-range global weather forecasting,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Learning skillful medium-range global weather forecasting,

Reference 7

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This paper cites Highly accurate protein structure prediction with al- phafold,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Highly accurate protein structure prediction with al- phafold,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.566644Z

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This paper cites Data-driven modeling and learning in science and engineering,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Data-driven modeling and learning in science and engineering,

Reference 9

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This paper cites Perspectives on the integration between first-principles and data-driven modeling,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Perspectives on the integration between first-principles and data-driven modeling,

Reference 10

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This paper cites It’s just not that simple: an empirical study of the accuracy-explainability trade-off in machine learning for public policy,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony It’s just not that simple: an empirical study of the accuracy-explainability trade-off in machine learning for public policy,

Reference 11

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This paper cites How explainability contributes to trust in ai,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony How explainability contributes to trust in ai,

Reference 12

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This paper cites Ai and science: what 1,600 researchers think,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Ai and science: what 1,600 researchers think,

Reference 13

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This paper cites Can we open the black box of AI?,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Can we open the black box of AI?,

Reference 14

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This paper cites KAN: Kolmogorov–Arnold net- works,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony KAN: Kolmogorov–Arnold net- works,

Reference 15

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Observation b96a922c-c25a-49e1-8072-6e48999ef913 · outbound

This paper cites KAN 2.0: Kolmogorov-Arnold Networks Meet Science.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony KAN 2.0: Kolmogorov-Arnold Networks Meet Science

Reference 16

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Observation 6b61f538-80bf-407d-92f1-4a5cbba4a339 · outbound

This paper cites From PINNs to PIKANs: Recent advances in physics-informed machine learning,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony From PINNs to PIKANs: Recent advances in physics-informed machine learning,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.497439Z

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This paper cites KAN-ODEs: Kolmogorov– Arnold network ordinary differential equations for learning dynamical systems and hidden physics,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony KAN-ODEs: Kolmogorov– Arnold network ordinary differential equations for learning dynamical systems and hidden physics,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.489891Z

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Observation c0172a78-17b8-48fc-a694-7883f87319cc · outbound

This paper cites Data-driven model discovery with Kolmogorov–Arnold networks,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Data-driven model discovery with Kolmogorov–Arnold networks,

Reference 19

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Observation fa2f52da-a65f-46ce-b43d-de2dada96bda · outbound

This paper cites Neural architecture search: A survey,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Neural architecture search: A survey,

Reference 20

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This paper cites Deeply- supervised nets,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Deeply- supervised nets,

Reference 21

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This paper cites BranchyNet: Fast inference via early exiting from deep neural networks,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony BranchyNet: Fast inference via early exiting from deep neural networks,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.458110Z

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Observation 26e05c21-834d-4509-aebb-36f3138eb3a3 · outbound

This paper cites Conditional deep learning for energy-efficient and enhanced pattern recognition,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Conditional deep learning for energy-efficient and enhanced pattern recognition,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.450898Z

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Observation 8dd56c5a-77d4-4143-ae6d-a03f35dcb416 · outbound

This paper cites Why should we add early exits to neural networks?,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Why should we add early exits to neural networks?,

Reference 24

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This paper cites Deep residual learning for image recognition,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Deep residual learning for image recognition,

Reference 25

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This paper cites Multilayer feedfor- ward networks are universal approximators,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Multilayer feedfor- ward networks are universal approximators,

Reference 26

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Unresolved cited work

Reference 27

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This paper cites On functions of three variables,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony On functions of three variables,

Reference 28

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Observation aebab636-0f9e-4e2f-b55d-1e29e66e7055 · outbound

This paper cites On the representations of continuous functions of many variables by superposition of continuous functions of one variable and addition,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony On the representations of continuous functions of many variables by superposition of continuous functions of one variable and addition,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.390140Z

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Observation 9ed08fd6-960e-4906-bb1e-e538186cbef0 · outbound

This paper cites Kolmogorov-Arnold Networks are Radial Basis Function Networks.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Kolmogorov-Arnold Networks are Radial Basis Function Networks

Reference 30

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This paper cites Enhancing Graph Collaborative Filtering with FourierKAN Feature Transformation.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Enhancing Graph Collaborative Filtering with FourierKAN Feature Transformation

Reference 31

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This paper cites SineKAN: Kolmogorov–Arnold networks using sinusoidal activation func- tions,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony SineKAN: Kolmogorov–Arnold networks using sinusoidal activation func- tions,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.370258Z

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This paper cites Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation

Reference 33

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This paper cites Wav-KAN: Wavelet Kolmogorov-Arnold Networks.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Wav-KAN: Wavelet Kolmogorov-Arnold Networks

Reference 34

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This paper cites On the limited memory BFGS method for large scale optimization,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony On the limited memory BFGS method for large scale optimization,

Reference 35

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Observation b5680a6b-8cd5-4b90-b31d-df6e9fcac213 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Adam: A Method for Stochastic Optimization

Reference 36

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This paper cites Bert loses patience: Fast and robust inference with early exit,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Bert loses patience: Fast and robust inference with early exit,

Reference 37

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Observation 385e5b8e-f6fe-4c1a-ae1f-12556b207e91 · outbound

This paper cites BERxiT: Early exiting for BERT with better fine-tuning and extension to regression,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony BERxiT: Early exiting for BERT with better fine-tuning and extension to regression,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.341403Z

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Observation 94d2fd23-3c22-4bfe-b48e-4b50da188693 · outbound

This paper cites Adaptive inference through early-exit networks: Design, challenges and directions,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Adaptive inference through early-exit networks: Design, challenges and directions,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.333226Z

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Observation 1dd4fd41-df39-4e05-a2ff-7d7d164fadec · outbound

This paper cites Early-exit deep neural network - a comprehensive survey,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Early-exit deep neural network - a comprehensive survey,

Reference 40

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Observation 4cf6d31c-d0f2-443c-9a19-949d81af7070 · outbound

This paper cites Densely connected convolutional networks,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Densely connected convolutional networks,

Reference 41

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Observation 06d65c58-dab0-4f3b-9c41-07010dcd5352 · outbound

This paper cites AI Feynman: A physics- inspired method for symbolic regression,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony AI Feynman: A physics- inspired method for symbolic regression,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.310432Z

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Observation aaeb8390-a965-4dbb-aeaa-7ff8fc9100b8 · outbound

This paper cites AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.291866Z

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Observation d75531c1-e74d-4025-8833-9dba91627539 · outbound

This paper cites Multiple-valued stationary state and its instabil- ity of the transmitted light by a ring cavity system,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Multiple-valued stationary state and its instabil- ity of the transmitted light by a ring cavity system,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.281858Z

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Observation 1002d8dd-f733-4bb4-957c-e0ce8e067651 · outbound

This paper cites Global dynamical behavior of the optical field in a ring cavity,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Global dynamical behavior of the optical field in a ring cavity,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.270974Z

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Observation 5a5edae7-640d-4c32-910e-00a0878257c8 · outbound

This paper cites Nonlinear dynamics and population disappearances,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Nonlinear dynamics and population disappearances,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.260579Z

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Observation 97c78513-78a8-420a-aaee-d43056fb5b97 · outbound

This paper cites Distal Interference: Exploring the Limits of Model-Based Continual Learning.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Distal Interference: Exploring the Limits of Model-Based Continual Learning

Reference 47

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Observation 3a146412-c1d8-450f-a830-c8b893fa13d7 · outbound

This paper cites Airfoil self-noise and prediction,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Airfoil self-noise and prediction,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.248578Z

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Observation de75c24a-b017-42a4-98b6-d34321a68c68 · outbound

This paper cites Local and global learning methods for predicting power of a combined gas & steam turbine,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Local and global learning methods for predicting power of a combined gas & steam turbine,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.238091Z

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Observation 289d3b0c-8fea-4261-ae1b-8254fe77b1c7 · outbound

This paper cites Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Prediction of full load electrical power output of a base load operated combined cycle power plant using machine learning methods,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.228227Z

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Observation 00f4535d-7a27-4029-a5ce-3d445dfff0d1 · outbound

This paper cites A data-driven statistical model for predicting the critical temperature of a superconductor,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony A data-driven statistical model for predicting the critical temperature of a superconductor,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.218427Z

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Observation 3a85051a-a598-4eb7-838c-b131538967d5 · outbound

This paper cites MDR SuperCon datasheet ver.240322.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony MDR SuperCon datasheet ver.240322

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.209685Z

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This paper cites The UCI machine learning repository,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony The UCI machine learning repository,

Reference 53

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This paper cites Ensemble learning: A survey,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Ensemble learning: A survey,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.188606Z

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Observation e26ed2e8-3947-45e2-94fd-071c86dd3933 · outbound

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Unresolved cited work

Reference 55

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This paper cites A review of uncertainty quantification in deep learning: Techniques, applications and challenges,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony A review of uncertainty quantification in deep learning: Techniques, applications and challenges,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.168395Z

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Observation 7da88c25-96a6-4719-950d-576277de856a · outbound

This paper cites Bayesian Kolmogorov Arnold Networks (Bayesian_KANs): A Probabilistic Approach to Enhance Accuracy and Interpretability.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Bayesian Kolmogorov Arnold Networks (Bayesian_KANs): A Probabilistic Approach to Enhance Accuracy and Interpretability

Reference 57

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Observation 8fe07d64-d00a-4e4e-93d1-bd0e265e4d30 · outbound

This paper cites Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning

Reference 58

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Observation 10818575-a76b-4cbf-b03d-185ec90eef80 · outbound

This paper cites DARTS: Differentiable architecture search,.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony DARTS: Differentiable architecture search,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.157665Z

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Observation 1a8d1f55-150f-4610-a6d2-3ae8ba5af3d8 · outbound

This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony PyTorch: An Imperative Style, High-Performance Deep Learning Library

Reference 60

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This paper cites FourierKAN.

Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony FourierKAN

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:11:04.147300Z

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Observation be778af0-1bb9-4976-b331-5b1bcfcba2f7 · outbound

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Multi-Exit Kolmogorov-Arnold Networks: enhancing accuracy and parsimony Unresolved cited work

Reference 2019

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