:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wyrod, Patrick, Chattopadhyay, Ashesh, Venturi, Daniele
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computational Physics
Online Access:	https://arxiv.org/abs/2512.24446
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

What You See is Not What You Get: Neural Partial Differential Equations and The Illusion of Learning
by: Mohan, Arvind, et al.
Published: (2024)

Towards physically consistent data-driven weather forecasting: Integrating data assimilation with equivariance-preserving deep spatial transformers
by: Chattopadhyay, Ashesh, et al.
Published: (2021)

Malliavin Calculus for Score-based Diffusion Models
by: Mirafzali, Ehsan, et al.
Published: (2025)

LUCIE-3D: A three-dimensional climate emulator for forced responses
by: Guan, Haiwen, et al.
Published: (2025)

LUCIE: A Lightweight Uncoupled ClImate Emulator with long-term stability and physical consistency for O(1000)-member ensembles
by: Guan, Haiwen, et al.
Published: (2024)

Fourier analysis of the physics of transfer learning for data-driven subgrid-scale models of ocean turbulence
by: Darman, Moein, et al.
Published: (2025)

Challenges of learning multi-scale dynamics with AI weather models: Implications for stability and one solution
by: Chattopadhyay, Ashesh, et al.
Published: (2023)

Can AI weather models predict out-of-distribution gray swan tropical cyclones?
by: Sun, Y. Qiang, et al.
Published: (2024)

Generative Lagrangian data assimilation for ocean dynamics under extreme sparsity
by: Asefi, Niloofar, et al.
Published: (2025)

MENO: Hybrid Matrix Exponential-based Neural Operator for Stiff ODEs. Application to Thermochemical Kinetics
by: Zanardi, Ivan, et al.
Published: (2025)

Uncertainty propagation in feed-forward neural network models
by: Diamzon, Jeremy, et al.
Published: (2025)

Interpretable structural model error discovery from sparse assimilation increments using spectral bias-reduced neural networks: A quasi-geostrophic turbulence test case
by: Mojgani, Rambod, et al.
Published: (2023)

Skillful joint probabilistic weather forecasting from marginals
by: Alet, Ferran, et al.
Published: (2025)

Cross-Scale Reservoir Computing for large spatio-temporal forecasting and modeling
by: Alboré, Nicola, et al.
Published: (2025)

OceanNet: A principled neural operator-based digital twin for regional oceans
by: Chattopadhyay, Ashesh, et al.
Published: (2023)

Accurate generation of stochastic dynamics based on multi-model Generative Adversarial Networks
by: Lanzoni, Daniele, et al.
Published: (2023)

Dynamical errors in machine learning forecasts
by: Fang, Zhou, et al.
Published: (2025)

Zero-shot forecasting of chaotic systems
by: Zhang, Yuanzhao, et al.
Published: (2024)

Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models
by: Zhang, Hanlin, et al.
Published: (2023)

Robustness of AI-based weather forecasts in a changing climate
by: Rackow, Thomas, et al.
Published: (2024)

Partition of Unity Physics-Informed Neural Networks (POU-PINNs): An Unsupervised Framework for Physics-Informed Domain Decomposition and Mixtures of Experts
by: Rodriguez, Arturo, et al.
Published: (2024)

Improved deep learning of chaotic dynamical systems with multistep penalty losses
by: Chakraborty, Dibyajyoti, et al.
Published: (2024)

Robust Design and Evaluation of Predictive Algorithms under Unobserved Confounding
by: Rambachan, Ashesh, et al.
Published: (2022)

High-Resolution Climate Projections Using Diffusion-Based Downscaling of a Lightweight Climate Emulator
by: Guan, Haiwen, et al.
Published: (2026)

A deep learning framework for jointly solving transient Fokker-Planck equations with arbitrary parameters and initial distributions
by: Wang, Xiaolong, et al.
Published: (2026)

A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators
by: Rautela, Mahindra, et al.
Published: (2024)

Weighted Flow Matching and Physics-Informed Nonlinear Filtering for Parameter Estimation in Digital Twins
by: Yanik, Yasar, et al.
Published: (2026)

Online detection of forecast model inadequacies using forecast errors
by: Grundy, Thomas, et al.
Published: (2025)

A case study of spatiotemporal forecasting techniques for weather forecasting
by: Sofi, Shakir Showkat, et al.
Published: (2022)

Simultaneous emulation and downscaling with physically-consistent deep learning-based regional ocean emulators
by: Lupin-Jimenez, Leonard, et al.
Published: (2025)

denoiSplit: a method for joint microscopy image splitting and unsupervised denoising
by: Ashesh, Ashesh, et al.
Published: (2024)

Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecasting
by: Rice, Julian, et al.
Published: (2020)

A Malliavin calculus approach to score functions in diffusion generative models
by: Mirafzali, Ehsan, et al.
Published: (2025)

SHARP-QoS: Sparsely-gated Hierarchical Adaptive Routing for joint Prediction of QoS
by: Kumar, Suraj, et al.
Published: (2025)

Deconstructing Recurrence, Attention, and Gating: Investigating the transferability of Transformers and Gated Recurrent Neural Networks in forecasting of dynamical systems
by: Heidenreich, Hunter S., et al.
Published: (2024)

Tensor approximation of functional differential equations
by: Rodgers, Abram, et al.
Published: (2024)

Stabilizing Backpropagation Through Time to Learn Complex Physics
by: Schnell, Patrick, et al.
Published: (2024)

Ensemble forecasts in reproducing kernel Hilbert space family
by: Dufée, Benjamin, et al.
Published: (2022)

Skillful high-resolution weather forecasting independent of physical models
by: Zhao, Pengcheng, et al.
Published: (2026)

Holographic generative flows with AdS/CFT
by: Mirafzali, Ehsan, et al.
Published: (2026)