Cover Image

The Physics-Informed Neural Network Gravity Model: Generation III

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Martin, John, Schaub, Hanspeter
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Geophysics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Gabor-Enhanced Physics-Informed Neural Networks for Fast Simulations of Acoustic Wavefields
by: Abedi, Mohammad Mahdi, et al.
Published: (2025)

Thermal Earth Model for the Conterminous United States Using an Interpolative Physics-Informed Graph Neural Network (InterPIGNN)
by: Aljubran, Mohammad J., et al.
Published: (2024)

Direct Estimation of Porosity from Seismic Data using Rock and Wave Physics Informed Neural Networks (RW-PINN)
by: Vashisth, Divakar, et al.
Published: (2022)

A Green-Integral-Constrained Neural Solver with Stochastic Physics-Informed Regularization
by: Abedi, Mohammad Mahdi, et al.
Published: (2026)

Physics-Informed Neural Networks for Predicting Hydrogen Sorption in Geological Formations: Thermodynamically Constrained Deep Learning Integrating Classical Adsorption Theory
by: Nooraiepour, Mohammad, et al.
Published: (2026)

Physics-Informed Linear Model (PILM): Analytical Representations and Application to Crustal Strain Rate Estimation
by: Okazaki, Tomohisa
Published: (2025)

An End-to-End Differentiable, Graph Neural Network-Embedded Pore Network Model for Permeability Prediction
by: Zhao, Qingqi, et al.
Published: (2025)

Data-Driven Dynamic Friction Models based on Recurrent Neural Networks
by: Cortes, Gaëtan, et al.
Published: (2024)

Physics-Trained Neural Network as Inverse Problem Solver for Potential Fields: An Example of Downward Continuation between Arbitrary Surfaces
by: Sun, Jing, et al.
Published: (2025)

Extrapolability Improvement of Machine Learning-Based Evapotranspiration Models via Domain-Adversarial Neural Networks
by: Shi, Haiyang
Published: (2024)

Towards Understanding the Benefits of Neural Network Parameterizations in Geophysical Inversions: A Study With Neural Fields
by: Xu, Anran, et al.
Published: (2025)

Double Difference Earthquake Location with Graph Neural Networks
by: McBrearty, Ian W., et al.
Published: (2024)

Multi-Constitutive Neural Network for Large Deformation Poromechanics Problem
by: Zhang, Qi, et al.
Published: (2020)

Global River Forecasting with a Topology-Informed AI Foundation Model
by: Ren, Hancheng, et al.
Published: (2026)

Path Signatures and Graph Neural Networks for Slow Earthquake Analysis: Better Together?
by: Riess, Hans, et al.
Published: (2024)

Broadband Ground Motion Synthesis via Generative Adversarial Neural Operators: Development and Validation
by: Shi, Yaozhong, et al.
Published: (2023)

A Test-Time Learning Approach to Reparameterize the Geophysical Inverse Problem with a Convolutional Neural Network
by: Xu, Anran, et al.
Published: (2023)

Transcending Classical Neural Network Boundaries: A Quantum-Classical Synergistic Paradigm for Seismic Data Processing
by: Yuan, Zhengyi, et al.
Published: (2026)

Data-Driven and Theory-Guided Pseudo-Spectral Seismic Imaging Using Deep Neural Network Architectures
by: Zerafa, Christopher
Published: (2025)

Learning Generative Models for Lumped Rainfall-Runoff Modeling
by: Yang, Yang, et al.
Published: (2023)

EFKAN: A KAN-Integrated Neural Operator For Efficient Magnetotelluric Forward Modeling
by: Wang, Feng, et al.
Published: (2025)

Graph Network Surrogate Model for Subsurface Flow Optimization
by: Tang, Haoyu, et al.
Published: (2023)

Fourier Neural Operator Surrogate Model to Predict 3D Seismic Waves Propagation
by: Lehmann, Fanny, et al.
Published: (2023)

Enhanced 3D Gravity Inversion Using ResU-Net with Density Logging Constraints: A Dual-Phase Training Approach
by: Dong, Siyuan, et al.
Published: (2026)

Latent Diffusion Model for Conditional Reservoir Facies Generation
by: Lee, Daesoo, et al.
Published: (2023)

Multimodal Atmospheric Super-Resolution With Deep Generative Models
by: Chakraborty, Dibyajyoti, et al.
Published: (2025)

Generative Latent Diffusion Model for Inverse Modeling and Uncertainty Analysis in Geological Carbon Sequestration
by: Feng, Zhao, et al.
Published: (2025)

Toward Routing River Water in Land Surface Models with Recurrent Neural Networks
by: Lima, Mauricio, et al.
Published: (2024)

Short-term Streamflow and Flood Forecasting based on Graph Convolutional Recurrent Neural Network and Residual Error Learning
by: Pan, Xiyu, et al.
Published: (2024)

Physical Sensitivity Kernels Can Emerge in Data-Driven Forward Models: Evidence From Surface-Wave Dispersion
by: Yu, Ziye, et al.
Published: (2026)

Ambient Noise Full Waveform Inversion with Neural Operators
by: Zou, Caifeng, et al.
Published: (2025)

GenAI4UQ: A Software for Inverse Uncertainty Quantification Using Conditional Generative Models
by: Fan, Ming, et al.
Published: (2024)

An Attention-Based Algorithm for Gravity Adaptation Zone Calibration
by: Yu, Chen
Published: (2024)

Time Series Foundation Models and Deep Learning Architectures for Earthquake Temporal and Spatial Nowcasting
by: Jafari, Alireza, et al.
Published: (2024)

Seismic event classification with a lightweight Fourier Neural Operator model
by: Abdullin, Ayrat, et al.
Published: (2025)

Performance of Machine Learning Methods for Gravity Inversion: Successes and Challenges
by: Negahdari, Vahid, et al.
Published: (2025)

Parameter-Efficient Transfer Learning for Microseismic Phase Picking Using a Neural Operator
by: Abdullin, Ayrat, et al.
Published: (2025)

Multiple-Input Fourier Neural Operator (MIFNO) for source-dependent 3D elastodynamics
by: Lehmann, Fanny, et al.
Published: (2024)

Salt-Rock Creep Deformation Forecasting Using Deep Neural Networks and Analytical Models for Subsurface Energy Storage Applications
by: Shukla, Pradeep Kumar, et al.
Published: (2025)

Modeling groundwater levels in California's Central Valley by hierarchical Gaussian process and neural network regression
by: Pradhan, Anshuman, et al.
Published: (2023)