From the 1 of 28 linked papers with an AI index.
28 papers
Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Video Flow-matching
Dibyajyoti Chakraborty, Romit Maulik
Data assimilation (DA) uses Bayesian inference to update the state of a numerical forecast model with observed data. In this study, we propose a fundamentally different, unified ap…
A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series
Xuyang Li, John Harlim, Dibyajyoti Chakraborty +1
The paper introduces a weak-form loss function for training Neural ODEs that improves learning of chaotic dynamics from noisy time‑series data, yielding more stable and accurate sh…
Scale-Aware Learning of Chaotic Dynamics on Unstructured Meshes via Binned Spectral Losses
Kanad Sen, Romit Maulik
Surrogate modeling for high-dimensional nonlinear dynamical systems that exhibit chaos requires mechanisms that preserve not only pointwise accuracy but also the scale-dependent st…
High-Resolution Climate Projections Using Diffusion-Based Downscaling of a Lightweight Climate Emulator
Haiwen Guan, Dibyajyoti Chakraborty, Moein Darman +3
The proliferation of data-driven models in weather and climate sciences has marked a significant paradigm shift, with advanced models demonstrating exceptional skill in medium-rang…
Multiscale Hypersonic Boundary Layer Reconstruction via Spectral Binning and Subdomain-wise Conditional Diffusion
Hojin Kim, Dibyajyoti Chakraborty, Takahiko Toki +2
We propose a multiscale probabilistic reconstruction framework for hypersonic Couette flow, where near-wall states are inferred from limited top-wall observations using conditional…
Deep Learning of Solver-Aware Turbulence Closures from Nudged LES Dynamics
Ashwin Suriyanarayanan, Dibyajyoti Chakraborty, Romit Maulik
The differentiable physics paradigm may be leveraged as an a-posteriori approach for discovering turbulence closure models by embedding a neural network parameterization directly i…