Image de couverture de livre

Enhancing Symbolic Regression and Universal Physics-Informed Neural Networks with Dimensional Analysis

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Podina, Lena, Darooneh, Diba, Grewal, Joshveer, Kohandel, Mohammad
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Learning Chemotherapy Drug Action via Universal Physics-Informed Neural Networks
par: Podina, Lena, et autres
Publié: (2024)

Conformalized Physics-Informed Neural Networks
par: Podina, Lena, et autres
Publié: (2024)

Denoising Diffusion Restoration Tackles Forward and Inverse Problems for the Laplace Operator
par: Mukherjee, Amartya, et autres
Publié: (2024)

An Architecture-Led Hybrid Report on Body Language Detection Project
par: Tong, Thomson, et autres
Publié: (2025)

IP-Basis PINNs: Efficient Multi-Query Inverse Parameter Estimation
par: Manor, Shalev, et autres
Publié: (2025)

A Unified Framework for Simultaneous Parameter and Function Discovery in Differential Equations
par: Manor, Shalev, et autres
Publié: (2025)

Operator Feature Neural Network for Symbolic Regression
par: Deng, Yusong, et autres
Publié: (2024)

Neural Symbolic Regression of Complex Network Dynamics
par: Qiu, Haiquan, et autres
Publié: (2024)

Symbolic Regression via Neural Networks
par: Boddupalli, Nibodh, et autres
Publié: (2026)

Gabor-Enhanced Physics-Informed Neural Networks for Fast Simulations of Acoustic Wavefields
par: Abedi, Mohammad Mahdi, et autres
Publié: (2025)

Learning Interpretable Network Dynamics via Universal Neural Symbolic Regression
par: Hu, Jiao, et autres
Publié: (2024)

PruneSymNet: A Symbolic Neural Network and Pruning Algorithm for Symbolic Regression
par: Wu, Min, et autres
Publié: (2024)

Bayesian Symbolic Regression for Missing Physics
par: Strouwen, Arno
Publié: (2026)

Bayesian Physics Informed Neural Networks for Linear Inverse problems
par: Mohammad-Djafari, Ali
Publié: (2025)

Design Your Own Universe: A Physics-Informed Agnostic Method for Enhancing Graph Neural Networks
par: Shi, Dai, et autres
Publié: (2024)

Enhancing Physics-Informed Neural Networks Through Feature Engineering
par: Fazliani, Shaghayegh, et autres
Publié: (2025)

Scalable Neural Symbolic Regression using Control Variables
par: Chu, Xieting, et autres
Publié: (2023)

Separable DeepONet: Breaking the Curse of Dimensionality in Physics-Informed Machine Learning
par: Mandl, Luis, et autres
Publié: (2024)

StruSR: Structure-Aware Symbolic Regression with Physics-Informed Taylor Guidance
par: Gong, Yunpeng, et autres
Publié: (2025)

A Novel Approach to Image EEG Sleep Data for Improving Quality of Life in Patients Suffering From Brain Injuries Using DreamDiffusion
par: Fahim, David, et autres
Publié: (2024)

Model Based and Physics Informed Deep Learning Neural Network Structures
par: Mohammad-Djafari, Ali, et autres
Publié: (2024)

Statistical Learning Analysis of Physics-Informed Neural Networks
par: Barajas-Solano, David A.
Publié: (2026)

ISR: Invertible Symbolic Regression
par: Tohme, Tony, et autres
Publié: (2024)

Meta-Inverse Physics-Informed Neural Networks for High-Dimensional Ordinary Differential Equations
par: Wei, Zhao, et autres
Publié: (2026)

Adaptive Physics-Informed Neural Networks with Multi-Category Feature Engineering for Hydrogen Sorption Prediction in Clays, Shales, and Coals
par: Nooraiepour, Mohammad, et autres
Publié: (2025)

Parsing the Language of Expression: Enhancing Symbolic Regression with Domain-Aware Symbolic Priors
par: Huang, Sikai, et autres
Publié: (2025)

eXtended Physics Informed Neural Network Method for Fracture Mechanics Problems
par: Lotfalian, Amin, et autres
Publié: (2025)

An Efficient and Generalizable Symbolic Regression Method for Time Series Analysis
par: Xie, Yi, et autres
Publié: (2024)

Physics-Informed Neural Networks with Unknown Partial Differential Equations: an Application in Multivariate Time Series
par: Mortezanejad, Seyedeh Azadeh Fallah, et autres
Publié: (2025)

Bayesian Physics-Informed Neural Networks for Inverse Problems (BPINN-IP): Application in Infrared Image Processing
par: Mohammad-Djafari, Ali, et autres
Publié: (2025)

SPINEX_ Symbolic Regression: Similarity-based Symbolic Regression with Explainable Neighbors Exploration
par: Naser, MZ, et autres
Publié: (2024)

The Road to Learning Explainable Inverse Kinematic Models: Graph Neural Networks as Inductive Bias for Symbolic Regression
par: Pandey, Pravin, et autres
Publié: (2025)

Diffusion-Based Symbolic Regression
par: Bastiani, Zachary, et autres
Publié: (2025)

Dimension Reduction for Symbolic Regression
par: Kahlmeyer, Paul, et autres
Publié: (2025)

Decomposable Neuro Symbolic Regression
par: Morales, Giorgio, et autres
Publié: (2025)

Fast Symbolic Regression Benchmarking
par: Martinek, Viktor
Publié: (2025)

Data-Informed Model Complexity Metric for Optimizing Symbolic Regression Models
par: Haut, Nathan, et autres
Publié: (2025)

An Empirical Investigation of Neural ODEs and Symbolic Regression for Dynamical Systems
par: Ioannou, Panayiotis, et autres
Publié: (2026)

Tensor-on-tensor Regression Neural Networks for Process Modeling with High-dimensional Data
par: Wang, Qian, et autres
Publié: (2025)

Can Test-time Computation Mitigate Reproduction Bias in Neural Symbolic Regression?
par: Sato, Shun, et autres
Publié: (2025)