Copertina

jinns: a JAX Library for Physics-Informed Neural Networks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Gangloff, Hugo, Jouvin, Nicolas
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Effective regions and kernels in continuous sparse regularisation, with application to sketched mixtures
di: De Castro, Yohann, et al.
Pubblicazione: (2025)

SNNAX -- Spiking Neural Networks in JAX
di: Lohoff, Jamie, et al.
Pubblicazione: (2024)

gfnx: Fast and Scalable Library for Generative Flow Networks in JAX
di: Tiapkin, Daniil, et al.
Pubblicazione: (2025)

HyperSBINN: A Hypernetwork-Enhanced Systems Biology-Informed Neural Network for Efficient Drug Cardiosafety Assessment
di: Soukarieh, Inass, et al.
Pubblicazione: (2024)

On the Role of Consistency Between Physics and Data in Physics-Informed Neural Networks
di: Becerra-Zuniga, Nicolás, et al.
Pubblicazione: (2026)

A new class of Markov random fields enabling lightweight sampling
di: Courbot, Jean-Baptiste, et al.
Pubblicazione: (2025)

jNO: A JAX Library for Neural Operator and Foundation Model Training
di: Armbruster, Leon, et al.
Pubblicazione: (2026)

Conformalized Physics-Informed Neural Networks
di: Podina, Lena, et al.
Pubblicazione: (2024)

Benchmarking Physics-Informed Neural Networks and Boundary Elements Methods for Wave Scattering
di: Rincón-Cardeno, Oscar, et al.
Pubblicazione: (2025)

BlackJAX: Composable Bayesian inference in JAX
di: Cabezas, Alberto, et al.
Pubblicazione: (2024)

Recent Advances of NeuroDiffEq -- An Open-Source Library for Physics-Informed Neural Networks
di: Liu, Shuheng, et al.
Pubblicazione: (2025)

Preconditioning for Physics-Informed Neural Networks
di: Liu, Songming, et al.
Pubblicazione: (2024)

Physics-Informed Neural Networks and Extensions
di: Raissi, Maziar, et al.
Pubblicazione: (2024)

Complex Physics-Informed Neural Network
di: Si, Chenhao, et al.
Pubblicazione: (2025)

Functional Tensor Decompositions for Physics-Informed Neural Networks
di: Vemuri, Sai Karthikeya, et al.
Pubblicazione: (2024)

Architectural Strategies for the optimization of Physics-Informed Neural Networks
di: Saratchandran, Hemanth, et al.
Pubblicazione: (2024)

The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks
di: Bonfanti, Andrea, et al.
Pubblicazione: (2024)

Fourier Feature Pyramids for Physics-Informed Neural Networks
di: Zhao, Brandon, et al.
Pubblicazione: (2026)

Physical Informed Neural Networks for modeling ocean pollutant
di: Battina, Karishma, et al.
Pubblicazione: (2025)

CLAX: Fast and Flexible Neural Click Models in JAX
di: Hager, Philipp, et al.
Pubblicazione: (2025)

SoftJAX & SoftTorch: Empowering Automatic Differentiation Libraries with Informative Gradients
di: Paulus, Anselm, et al.
Pubblicazione: (2026)

Perception-Informed Neural Networks: Beyond Physics-Informed Neural Networks
di: Mazandarani, Mehran, et al.
Pubblicazione: (2025)

MPX: Mixed Precision Training for JAX
di: Gräfe, Alexander, et al.
Pubblicazione: (2025)

DrJAX: Scalable and Differentiable MapReduce Primitives in JAX
di: Rush, Keith, et al.
Pubblicazione: (2024)

Densely Multiplied Physics Informed Neural Networks
di: Jiang, Feilong, et al.
Pubblicazione: (2024)

Dual-Balancing for Physics-Informed Neural Networks
di: Zhou, Chenhong, et al.
Pubblicazione: (2025)

Randomized Physics-Informed Neural Networks for Bayesian Data Assimilation
di: Zong, Yifei, et al.
Pubblicazione: (2024)

Physics-Informed Neural Network for Concrete Manufacturing Process Optimization
di: Varghese, Sam, et al.
Pubblicazione: (2024)

RoPINN: Region Optimized Physics-Informed Neural Networks
di: Wu, Haixu, et al.
Pubblicazione: (2024)

Guaranteeing Conservation Laws with Projection in Physics-Informed Neural Networks
di: Baez, Anthony, et al.
Pubblicazione: (2024)

Coordinate Encoding on Linear Grids for Physics-Informed Neural Networks
di: Tsuchino, Tetsuro, et al.
Pubblicazione: (2026)

Enhancing Physics-Informed Neural Networks Through Feature Engineering
di: Fazliani, Shaghayegh, et al.
Pubblicazione: (2025)

Guaranteeing Conservation of Integrals with Projection in Physics-Informed Neural Networks
di: Baez, Anthony, et al.
Pubblicazione: (2025)

Physics-Informed Neural Networks and Neural Operators for Parametric PDEs
di: Zhang, Zhuo, et al.
Pubblicazione: (2025)

Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks
di: Rohrhofer, Franz M., et al.
Pubblicazione: (2021)

laplax -- Laplace Approximations with JAX
di: Weber, Tobias, et al.
Pubblicazione: (2025)

Evidential Physics-Informed Neural Networks
di: Tan, Hai Siong, et al.
Pubblicazione: (2025)

Hard Constraint Projection in a Physics Informed Neural Network
di: Horne, Miranda J. S., et al.
Pubblicazione: (2026)

Structure-Preserving Physics-Informed Neural Networks With Energy or Lyapunov Structure
di: Chu, Haoyu, et al.
Pubblicazione: (2024)

PinnDE: Physics-Informed Neural Networks for Solving Differential Equations
di: Matthews, Jason, et al.
Pubblicazione: (2024)