Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators | Paper Citation Record

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators write newline

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This paper cites L., Gruber, L., Holzleitner, M., and Brandstetter, J.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators L., Gruber, L., Holzleitner, M., and Brandstetter, J

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Y., Deiseroth, B., Cruz-Salinas, A

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators B., Hanin, B., and Pehlevan, C

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This paper cites B., Levine, M.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators B., Levine, M

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This paper cites Choose a transformer: Fourier or galerkin.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Choose a transformer: Fourier or galerkin

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This paper cites Principled architecture-aware scaling of hyperparameters.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Principled architecture-aware scaling of hyperparameters

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators and Mishra, S

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This paper cites Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster

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This paper cites Physics-informed inference time scaling via simulation-calibrated scientific machine learning.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Physics-informed inference time scaling via simulation-calibrated scientific machine learning

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators J., Zhao, J., Kossaifi, J., Li, Z., and Anandkumar, A

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Multiwavelet-based operator learning for differential equations

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This paper cites Solving high-dimensional partial differential equations using deep learning.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Solving high-dimensional partial differential equations using deep learning

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This paper cites Learning physics-informed neural networks without stacked back-propagation.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Learning physics-informed neural networks without stacked back-propagation

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Scaling Laws for Autoregressive Generative Modeling

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Training Compute-Optimal Large Language Models

Reference 16

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Meta-auto-decoder for solving parametric partial differential equations

Reference 17

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators and Karakida, R

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This paper cites Scaling Scaling Laws with Board Games.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Scaling Scaling Laws with Board Games

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Scaling Laws for Neural Language Models

Reference 20

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This paper cites Solving parametric pde problems with artificial neural networks.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Solving parametric pde problems with artificial neural networks

Reference 21

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators and Kang, M

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Adam: A Method for Stochastic Optimization

Reference 23

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators A., Alieva, A., Wang, Q., Brenner, M

Reference 24

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This paper cites Understanding the expressivity and trainability of fourier neural operator: A mean-field perspective.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Understanding the expressivity and trainability of fourier neural operator: A mean-field perspective

Reference 25

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators On universal approximation and error bounds for fourier neural operators

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Neural operator: Learning maps between function spaces with applications to pdes

Reference 27

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators and Dik, M

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Codepde: An inference framework for llm-driven pde solver generation

Reference 29

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Multipole graph neural operator for parametric partial differential equations

Reference 30

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators B., Azizzadenesheli, K., liu, B., Bhattacharya, K., Stuart, A., and Anandkumar, A

Reference 31

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Physics-informed neural operator for learning partial differential equations

Reference 32

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators An Empirical Study of $\mu$P Learning Rate Transfer

Reference 33

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators PDE -net: Learning PDE s from data

Reference 34

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Pde-net 2.0: Learning pdes from data with a numeric-symbolic hybrid deep network

Reference 35

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Super consistency of neural network landscapes and learning rate transfer

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Gpt-4 technical report, 2023

Reference 38

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators On the difficulty of training recurrent neural networks

Reference 39

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Py T orch: An imperative style, high-performance deep learning library

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators and Xie, S

Reference 41

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators A., George, R

Reference 42

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Unresolved cited work

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators and Spiliopoulos, K

Reference 45

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

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This paper cites High-dimensional probability: An introduction with applications in data science, volume 47.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators High-dimensional probability: An introduction with applications in data science, volume 47

Reference 47

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This paper cites Is L^2 physics-informed loss always suitable for training physics-informed neural network? In Advances in Neural Information Processing Systems, 2022.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Is L^2 physics-informed loss always suitable for training physics-informed neural network? In Advances in Neural Information Processing Systems, 2022

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Coarse Graining with Neural Operators for Simulating Chaotic Systems

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models

Reference 50

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators and Hu, E

Reference 51

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Tensor programs VI : Feature learning in infinite depth neural networks

Reference 53

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Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Pdeformer: Towards a foundation model for one-dimensional partial differential equations

Reference 54

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This paper cites Scaling Autoregressive Models for Content-Rich Text-to-Image Generation.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

Reference 55

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This paper cites Weak adversarial networks for high-dimensional partial differential equations.

Maximal Update Parametrization and Zero-Shot Hyperparameter Transfer for Fourier Neural Operators Weak adversarial networks for high-dimensional partial differential equations

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