:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Guan, Haiwen, Darman, Moein, Chakraborty, Dibyajyoti, Arcomano, Troy, Chattopadhyay, Ashesh, Maulik, Romit
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2602.13416
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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)

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

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

Divide And Conquer: Learning Chaotic Dynamical Systems With Multistep Penalty Neural Ordinary Differential Equations
by: Chakraborty, Dibyajyoti, et al.
Published: (2024)

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

Adaptive Diffusion Posterior Sampling for Data and Model Fusion of Complex Nonlinear Dynamical Systems
by: Chakraborty, Dibyajyoti, et al.
Published: (2026)

SC3D: Dynamic and Differentiable Causal Discovery for Temporal and Instantaneous Graphs
by: Das, Sourajit, et al.
Published: (2026)

Binned Spectral Power Loss for Improved Prediction of Chaotic Systems
by: Chakraborty, Dibyajyoti, et al.
Published: (2025)

Deep Learning of Solver-Aware Turbulence Closures from Nudged LES Dynamics
by: Suriyanarayanan, Ashwin, et al.
Published: (2026)

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

Differentiable Turbulence: Closure as a partial differential equation constrained optimization
by: Shankar, Varun, et al.
Published: (2023)

A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series
by: Li, Xuyang, et al.
Published: (2025)

A note on the error analysis of data-driven closure models for large eddy simulations of turbulence
by: Chakraborty, Dibyajyoti, et al.
Published: (2024)

MoWE : A Mixture of Weather Experts
by: Chakraborty, Dibyajyoti, et al.
Published: (2025)

SALSA-RL: Stability Analysis in the Latent Space of Actions for Reinforcement Learning
by: Li, Xuyang, et al.
Published: (2025)

Interpretable Diagnostics and Adaptive Data Assimilation for Neural ODEs via Discrete Empirical Interpolation
by: Kim, Hojin, et al.
Published: (2025)

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

Generative Diffusion-based Downscaling for Climate
by: Watt, Robbie A., et al.
Published: (2024)

Scaling transformer neural networks for skillful and reliable medium-range weather forecasting
by: Nguyen, Tung, et al.
Published: (2023)

A competitive baseline for deep learning enhanced data assimilation using conditional Gaussian ensemble Kalman filtering
by: Malik, Zachariah, et al.
Published: (2024)

Higher order quantum reservoir computing for non-intrusive reduced-order models
by: Jain, Vinamr, et al.
Published: (2024)

Leveraging Interpolation Models and Error Bounds for Verifiable Scientific Machine Learning
by: Chang, Tyler, et al.
Published: (2024)

Vision Transformers for Multi-Variable Climate Downscaling: Emulating Regional Climate Models with a Shared Encoder and Multi-Decoder Architecture
by: Merizzi, Fabio, et al.
Published: (2025)

FIGNN: Feature-Specific Interpretability for Graph Neural Network Surrogate Models
by: Raut, Riddhiman, et al.
Published: (2025)

Capturing Climatic Variability: Using Deep Learning for Stochastic Downscaling
by: Daust, Kiri, et al.
Published: (2024)

Interpretable A-posteriori Error Indication for Graph Neural Network Surrogate Models
by: Barwey, Shivam, et al.
Published: (2023)

CondensNet: Enabling stable long-term climate simulations via hybrid deep learning models with adaptive physical constraints
by: Wang, Xin, et al.
Published: (2025)

Semi-Implicit Neural Ordinary Differential Equations
by: Zhang, Hong, et al.
Published: (2024)

Swift: An Autoregressive Consistency Model for Efficient Weather Forecasting
by: Stock, Jason, et al.
Published: (2025)

SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators
by: Duncan, James P. C., et al.
Published: (2025)

Hard-Constrained Deep Learning for Climate Downscaling
by: Harder, Paula, et al.
Published: (2022)

Deep Learning-Driven Downscaling for Climate Risk Assessment of Projected Temperature Extremes in the Nordic Region
by: Loganathan, Parthiban, et al.
Published: (2025)

Generalizable data-driven turbulence closure modeling on unstructured grids with differentiable physics
by: Kim, Hojin, et al.
Published: (2023)

Self Supervised Vision for Climate Downscaling
by: Singh, Karandeep, et al.
Published: (2024)

Physics-Constrained Adaptive Flow Matching for Climate Downscaling
by: Debeire, Kevin, et al.
Published: (2026)

Localized PCA-Net Neural Operators for Scalable Solution Reconstruction of Elliptic PDEs
by: Dhingra, Mrigank, et al.
Published: (2025)

Assessing the Geographic Generalization and Physical Consistency of Generative Models for Climate Downscaling
by: Saccardi, Carlo, et al.
Published: (2025)

Diffusion Model-based Probabilistic Downscaling for 180-year East Asian Climate Reconstruction
by: Ling, Fenghua, et al.
Published: (2024)

Bridging the Gap Between Climate Science and Machine Learning in Climate Model Emulation
by: Schmidt, Luca, et al.
Published: (2026)

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