303 citations · 2.2k across the 86 of their papers we have counts for
11 papers · 1 filter
Puncture Evolution with Physics-Informed Neural Networks
Estuti Shukla, Ashwin Suriyanarayanan, David Radice +2
We investigate the application of physics-informed neural networks (PINNs) to solve the vacuum Einstein equations in spherical symmetry. Our neural network architecture is designed…
Generative Atmospheric Super-Resolution from Heterogeneous In Situ Observations through Composable Interfaces
Yang Xu, Dibyajyoti Chakraborty, Haiwen Guan +2
Atmospheric observations are sparse, heterogeneous, and unevenly distributed, whereas many generative atmospheric models learn distributions over regularly gridded multivariate sta…
Hapi: A Multivariable Land-Surface Transformer for Medium-Range Hydrological Forecasting at Continental Scale
Hong Zhang, John K. Hutchison, Rao Kotamarthi +8
Accurate flood forecasts several days in advance are essential for flood control, water-resource management, and emergency response. A central challenge is to produce high-resoluti…
Improving Reduced-Order Rotating Detonation Engine Models with Data Assimilation and Machine Learning
Ashwin Suriyanarayanan, Romit Maulik
Rotating detonation engines (RDEs) exhibit strongly nonlinear, multiscale wave dynamics that set the observed thermal field. High-fidelity simulations (DNS/LES) resolve these struc…
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…
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…
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…
Adaptive Diffusion Posterior Sampling for Data and Model Fusion of Complex Nonlinear Dynamical Systems
Dibyajyoti Chakraborty, Hojin Kim, Romit Maulik
High-fidelity numerical simulations of chaotic, high dimensional nonlinear dynamical systems are computationally expensive, necessitating the development of efficient surrogate mod…
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…
SC3D: Dynamic and Differentiable Causal Discovery for Temporal and Instantaneous Graphs
Sourajit Das, Dibyajyoti Chakraborty, Romit Maulik
Discovering causal structures from multivariate time series is a key problem because interactions span across multiple lags and possibly involve instantaneous dependencies. Additio…