:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Abbasi, Jassem, Moseley, Ben, Kurotori, Takeshi, Jagtap, Ameya D., Kovscek, Anthony R., Hiorth, Aksel, Andersen, Pål Østebø
Format:	Preprint
Published:	2024
Subjects:	Computational Engineering, Finance, and Science
Online Access:	https://arxiv.org/abs/2410.20801
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Challenges and Advancements in Modeling Shock Fronts with Physics-Informed Neural Networks: A Review and Benchmarking Study
by: Abbasi, Jassem, et al.
Published: (2025)

Physical Activation Functions (PAFs): An Approach for More Efficient Induction of Physics into Physics-Informed Neural Networks (PINNs)
by: Abbasi, Jassem, et al.
Published: (2022)

PTL-PINNs: Perturbation-Guided Transfer Learning with Physics- Informed Neural Networks for Nonlinear Systems
by: Alexandrino, Duarte, et al.
Published: (2026)

Assessment of Guidewire‐Induced Deviation in Fractional Flow Reserve: Impact of Lesion Morphology and Pressure Guidewire Malposition
by: Reza Rasooli, et al.
Published: (2025)

The Imbibition Mechanism and the Calculation Method of Maximum Imbibition Length during the Hydraulic Fracturing
by: Zhongwei Wu, et al.
Published: (2024)

Hypersonic Flow Control: Generalized Deep Reinforcement Learning for Hypersonic Intake Unstart Control under Uncertainty
by: Mondal, Trishit, et al.
Published: (2026)

MARUT: An Exascale-Ready, GPU-Accelerated High-Order CFD Framework with AMR for High-Speed Flows and Finite-Rate Chemistry
by: Mondal, Trishit, et al.
Published: (2026)

Structural Identifiability and Comparative Calibration of Water Retention Curves for Imbibition in Porous Media
by: Bretti, Gabriella, et al.
Published: (2026)

Shocks Under Control: Taming Transonic Compressible Flow over an RAE2822 Airfoil with Deep Reinforcement Learning
by: Mondal, Trishit, et al.
Published: (2025)

FEKAN: Feature-Enriched Kolmogorov-Arnold Networks
by: Menon, Sidharth S., et al.
Published: (2026)

In Transformer We Trust? A Perspective on Transformer Architecture Failure Modes
by: Mondal, Trishit, et al.
Published: (2026)

Anant-Net: Breaking the Curse of Dimensionality with Scalable and Interpretable Neural Surrogate for High-Dimensional PDEs
by: Menon, Sidharth S., et al.
Published: (2025)

Multiscale Hyperbolic-Parabolic Models for Nonlinear Reactive Transport in Heterogeneously Fractured Porous Media
by: Mel'nyk, Taras, et al.
Published: (2026)

Pore‐Scale Modeling of Pressure‐Driven Flow and Spontaneous Imbibition in Fracturing‐Shut‐In‐Flowback Process of Tight Oil Reservoirs
by: Ninghong Jia, et al.
Published: (2024)

BubbleOKAN: A Physics-Informed Interpretable Neural Operator for High-Frequency Bubble Dynamics
by: Zhang, Yunhao, et al.
Published: (2025)

PINNs Failure Modes are Overfitting
by: Andersen, Nigel T., et al.
Published: (2026)

An Approximation Theory Perspective on Machine Learning
by: Mhaskar, Hrushikesh N., et al.
Published: (2025)

Recovery from Myalgic Encephalomyelitis/Chronic Fatigue syndrome developed after severe acute respiratory syndrome coronavirus 2 vaccination: A case report
by: Isaku Kurotori, et al.
Published: (2025)

Numerical Robustness of PINNs for Multiscale Transport Equations
by: Jesser, Alexander, et al.
Published: (2024)

Sensitivity of Trapping Efficiency and Relative Permeability to Experimental Methodology in Laboratory Core Flooding
by: Spurin, Catherine, et al.
Published: (2025)

An Interior Penalty Discontinuous Galerkin Method for an Interface Model of Flow in Fractured Porous Media
by: Liu, Yong, et al.
Published: (2024)

Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations
by: Moseley, Ben, et al.
Published: (2021)

Invited commentary to strengths and opportunities for improvement in surgical education in Ukraine: A qualitative study
by: Christine Gaarder, et al.
Published: (2024)

RiemannONets: Interpretable Neural Operators for Riemann Problems
by: Peyvan, Ahmad, et al.
Published: (2024)

Yield Stress Fluids Solidifying in Capillary Imbibition
by: Kim, Hanul, et al.
Published: (2023)

Deformation Dynamics of Nanopores upon Water Imbibition
by: Sanchez, Juan, et al.
Published: (2023)

Imbibition of Oil in Dry and Prewetted Calcite Nanopores
by: Ahmed, Ejaz, et al.
Published: (2025)

Adaptive Nonlinear Elimination Preconditioning for Transport in Fractured Porous Media
by: Chaabi, Omar, et al.
Published: (2025)

Variational Phase‐Field Fracture Approach in Reactive Porous Media
by: Mostafa Mollaali, et al.
Published: (2025)

Nonlinear Expectation Inference for Efficient Uncertainty Quantification and History Matching of Transient Darcy Flows in Porous Media with Random Parameters Under Distribution Uncertainty
by: Zhang, Zhao, et al.
Published: (2023)

Mesh-based Super-resolution of Detonation Flows with Multiscale Graph Transformers
by: Barwey, Shivam, et al.
Published: (2025)

Extended Physics Informed Neural Network for Hyperbolic Two-Phase Flow in Porous Media
by: Rehman, Saif Ur, et al.
Published: (2025)

Multiscale Supervised Unbalanced Optimal Transport Flow Matching
by: Peng, Qiangwei, et al.
Published: (2026)

Flow Through Porous Media at the Percolation Transition
by: Residori, Mirko, et al.
Published: (2024)

Extending quantum theory with AI-assisted deterministic game theory
by: Pauschitz, Florian, et al.
Published: (2026)

EnfoPath: Energy-Informed Analysis of Generative Trajectories in Flow Matching
by: Li, Ziyun, et al.
Published: (2025)

AQ-PINNs: Attention-Enhanced Quantum Physics-Informed Neural Networks for Carbon-Efficient Climate Modeling
by: Dutta, Siddhant, et al.
Published: (2024)

Hessian-Informed Flow Matching
by: Sprague, Christopher Iliffe, et al.
Published: (2024)

A Petrov‐Galerkin Dual‐Porosity Framework for Thermal Analysis of Fractured Porous Media
by: Mahtab Taghvaei, et al.
Published: (2025)

Geometry-aware PINNs for Turbulent Flow Prediction
by: Ghosh, Shinjan, et al.
Published: (2024)