:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Cooley, Madison, Shankar, Varun, Kirby, Robert M., Zhe, Shandian
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2410.03496
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

HyResPINNs: A Hybrid Residual Physics-Informed Neural Network Architecture Designed to Balance Expressiveness and Trainability
by: Cooley, Madison, et al.
Published: (2024)

Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
by: Cooley, Madison, et al.
Published: (2024)

Solving High Frequency and Multi-Scale PDEs with Gaussian Processes
by: Fang, Shikai, et al.
Published: (2023)

Multi-Resolution Active Learning of Fourier Neural Operators
by: Li, Shibo, et al.
Published: (2023)

Diffusion-Based Symbolic Regression
by: Bastiani, Zachary, et al.
Published: (2025)

StFT: Spatio-temporal Fourier Transformer for Long-term Dynamics Prediction
by: Long, Da, et al.
Published: (2025)

Invertible Fourier Neural Operators for Tackling Both Forward and Inverse Problems
by: Long, Da, et al.
Published: (2024)

SIFBench: An Extensive Benchmark for Fatigue Analysis
by: Gautam, Tushar, et al.
Published: (2025)

Complexity-Aware Deep Symbolic Regression with Robust Risk-Seeking Policy Gradients
by: Bastiani, Zachary, et al.
Published: (2024)

Graph-Based Operator Learning from Limited Data on Irregular Domains
by: Li, Yile, et al.
Published: (2025)

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications
by: Logakannan, Krishna Prasath, et al.
Published: (2025)

Deep Gaussian Processes for Functional Maps
by: Lowery, Matthew, et al.
Published: (2025)

Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning
by: Lowery, Matthew, et al.
Published: (2024)

Multi-Operator Few-Shot Learning for Generalization Across PDE Families
by: Li, Yile, et al.
Published: (2025)

Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels
by: Long, Da, et al.
Published: (2023)

Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data
by: Fang, Shikai, et al.
Published: (2023)

Arbitrarily Conditioned Hierarchical Flows for Spatiotemporal Events
by: Chen, Keyan, et al.
Published: (2026)

Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation
by: Long, Da, et al.
Published: (2024)

Improving PINNs By Algebraic Inclusion of Boundary and Initial Conditions
by: Ren, Mohan, et al.
Published: (2024)

Predicting Wave Reflection and Transmission in Heterogeneous Media via Fourier Operator-Based Transformer Modeling
by: Bai, Zhe, et al.
Published: (2026)

Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization
by: Xu, Zhitong, et al.
Published: (2024)

Toward Efficient Kernel-Based Solvers for Nonlinear PDEs
by: Xu, Zhitong, et al.
Published: (2024)

Ensemble and Mixture-of-Experts DeepONets For Operator Learning
by: Sharma, Ramansh, et al.
Published: (2024)

BayOTIDE: Bayesian Online Multivariate Time series Imputation with functional decomposition
by: Fang, Shikai, et al.
Published: (2023)

Fourier Learning Machines: Nonharmonic Fourier-Based Neural Networks for Scientific Machine Learning
by: Rubel, Mominul, et al.
Published: (2025)

Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
by: Shi, Xinxing, et al.
Published: (2024)

Spectrum Prediction in the Fractional Fourier Domain with Adaptive Filtering
by: Qin, Yanghao, et al.
Published: (2025)

RL-PINNs: Reinforcement Learning-Driven Adaptive Sampling for Efficient Training of PINNs
by: Song, Zhenao
Published: (2025)

FourierNAT: A Fourier-Mixing-Based Non-Autoregressive Transformer for Parallel Sequence Generation
by: Kiruluta, Andrew, et al.
Published: (2025)

Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
by: Lingsch, Levi, et al.
Published: (2023)

Quantum Fourier Transform Based Kernel for Solar Irrandiance Forecasting
by: Mechiche-Alami, Nawfel, et al.
Published: (2025)

Adaptive Interface-PINNs (AdaI-PINNs): An Efficient Physics-informed Neural Networks Framework for Interface Problems
by: Roy, Sumanta, et al.
Published: (2024)

Gradient Scaling Effects in Adaptive Spectral PINNs for Stiff Nonlinear ODEs
by: Yepes, Isabela M., et al.
Published: (2026)

Kronecker-Structured Nonparametric Spatiotemporal Point Processes
by: Xu, Zhitong, et al.
Published: (2026)

Tensor Gaussian Processes: Efficient Solvers for Nonlinear PDEs
by: Yuan, Qiwei, et al.
Published: (2025)

Adaptive Random Fourier Features Training Stabilized By Resampling With Applications in Image Regression
by: Kammonen, Aku, et al.
Published: (2024)

Fourier Basis Density Model
by: De la Fuente, Alfredo, et al.
Published: (2024)

Effective Probabilistic Time Series Forecasting with Fourier Adaptive Noise-Separated Diffusion
by: Wang, Xinyan, et al.
Published: (2025)

An Adaptive Random Fourier Features approach Applied to Learning Stochastic Differential Equations
by: Douglas, Owen, et al.
Published: (2025)

Isotropic Fourier Neural Operators
by: Staddon, Michael F.
Published: (2026)