:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Li, Yicen, Benitez, Jose Antonio Lara, Hong, Ruiyang, Kratsios, Anastasis, McNicholas, Paul David, de Hoop, Maarten Valentijn
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Computational Engineering, Finance, and Science Computation
Accesso online:	https://arxiv.org/abs/2602.23528
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Keep It Light! Simplifying Image Clustering Via Text-Free Adapters
di: Li, Yicen, et al.
Pubblicazione: (2025)

Generative Neural Operators of Log-Complexity Can Simultaneously Solve Infinitely Many Convex Programs
di: Kratsios, Anastasis, et al.
Pubblicazione: (2025)

Polynomial Scaling is Possible For Neural Operator Approximations of Structured Families of BSDEs
di: Furuya, Takashi, et al.
Pubblicazione: (2024)

Neural Operators Can Play Dynamic Stackelberg Games
di: Alvarez, Guillermo, et al.
Pubblicazione: (2024)

Classification Fields: Arbitrarily Fine Recursive Hierarchical Clustering From Few Examples
di: Li, Yicen, et al.
Pubblicazione: (2026)

SANOS Smooth strictly Arbitrage-free Non-parametric Option Surfaces
di: Buehler, Hans, et al.
Pubblicazione: (2026)

Designing Universal Causal Deep Learning Models: The Case of Infinite-Dimensional Dynamical Systems from Stochastic Analysis
di: Galimberti, Luca, et al.
Pubblicazione: (2022)

Bridging the Gap Between Approximation and Learning via Optimal Approximation by ReLU MLPs of Maximal Regularity
di: Hong, Ruiyang, et al.
Pubblicazione: (2024)

Mixture of Experts Softens the Curse of Dimensionality in Operator Learning
di: Kratsios, Anastasis, et al.
Pubblicazione: (2024)

Discovering the mechanics of ultra-low density elastomeric foams in elite-level racing shoes
di: McCulloch, Jeremy A., et al.
Pubblicazione: (2026)

Adaptive Coordinate Transforms for Neural Operators
di: Liu, Chaoyu, et al.
Pubblicazione: (2026)

Neural Preconditioning Operator for Efficient PDE Solves
di: Li, Zhihao, et al.
Pubblicazione: (2025)

On the Effectiveness of Neural Operators at Zero-Shot Weather Downscaling
di: Sinha, Saumya, et al.
Pubblicazione: (2024)

Discovering uncertainty: Gaussian constitutive neural networks with correlated weights
di: McCulloch, Jeremy A., et al.
Pubblicazione: (2025)

One model to solve them all: 2BSDE families via neural operators
di: Furuya, Takashi, et al.
Pubblicazione: (2025)

Enforcing the Principle of Locality for Physical Simulations with Neural Operators
di: Chen, Jiangce, et al.
Pubblicazione: (2024)

Neural Operator Representation of Granular Micromechanics-based Failure Envelope
di: Han, Jinkyo, et al.
Pubblicazione: (2026)

MNO : A Multi-modal Neural Operator for Parametric Nonlinear BVPs
di: Madala, Vamshi C., et al.
Pubblicazione: (2025)

Quantum Computing for Multi Period Asset Allocation
di: Sun, Queenie, et al.
Pubblicazione: (2024)

Learning to Control PDEs with Differentiable Predictive Control and Time-Integrated Neural Operators
di: Sarkar, Dibakar Roy, et al.
Pubblicazione: (2025)

Neural Chaos: A Spectral Stochastic Neural Operator
di: Bahmani, Bahador, et al.
Pubblicazione: (2025)

A Resolution Independent Neural Operator
di: Bahmani, Bahador, et al.
Pubblicazione: (2024)

Low-dimensional approximations of the conditional law of Volterra processes: a non-positive curvature approach
di: Arabpour, Reza, et al.
Pubblicazione: (2024)

Deep Neural Operator Enabled Concurrent Multitask Design for Multifunctional Metamaterials under Heterogeneous Fields
di: Lee, Doksoo, et al.
Pubblicazione: (2023)

A Generative Adversarial Graph Neural Network for Synthetic Time Series Data
di: Gregnanin, Marco, et al.
Pubblicazione: (2026)

The Statistical Significance of the Inclusion of Graph Neural Networks in the Financial Time Series Forecasting Problem
di: Gregnanin, Marco, et al.
Pubblicazione: (2026)

Discovering Flow Separation Control Strategies in 3D Wings via Deep Reinforcement Learning
di: Montalà, R., et al.
Pubblicazione: (2025)

Fourier Neural Operators for Structural Dynamics Models: Challenges, Limitations and Advantages of Using a Spectrogram Loss
di: Haghi, Rad, et al.
Pubblicazione: (2025)

Using Graph Neural Networks and Frequency Domain Data for Automated Operational Modal Analysis of Populations of Structures
di: Jian, Xudong, et al.
Pubblicazione: (2024)

Regret-Optimal Federated Transfer Learning for Kernel Regression with Applications in American Option Pricing
di: Yang, Xuwei, et al.
Pubblicazione: (2023)

Thermodynamically Consistent Hybrid and Permutation-Invariant Neural Yield Functions for Anisotropic Plasticity
di: Jadoon, Asghar A., et al.
Pubblicazione: (2025)

LRQ-Solver: A Transformer-Based Neural Operator for Fast and Accurate Solving of Large-scale 3D PDEs
di: Zeng, Peijian, et al.
Pubblicazione: (2025)

Simultaneously Solving Infinitely Many LQ Mean Field Games In Hilbert Spaces: The Power of Neural Operators
di: Firoozi, Dena, et al.
Pubblicazione: (2025)

A Unit-Cell Shape Optimization Approach for Maximizing Heat Transfer in Periodic Fin Arrays at Constant Solid Temperature
di: Blommaert, Maarten, et al.
Pubblicazione: (2025)

Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEs
di: Rezaei, Shahed, et al.
Pubblicazione: (2024)

Physics-informed Partitioned Coupled Neural Operator for Complex Networks
di: Wu, Weidong, et al.
Pubblicazione: (2024)

An Attention-based Spatio-Temporal Neural Operator for Evolving Physics
di: Karkaria, Vispi, et al.
Pubblicazione: (2025)

Tau-BNO: Brain Neural Operator for Tau Transport Model
di: Barron, Nuutti, et al.
Pubblicazione: (2026)

$ϕ-$DeepONet: A Discontinuity Capturing Neural Operator
di: Roy, Sumanta, et al.
Pubblicazione: (2026)

The Paradox Of Just-in-Time Liquidity in Decentralized Exchanges: More Providers Can Sometimes Mean Less Liquidity
di: Capponi, Agostino, et al.
Pubblicazione: (2023)