4 papers
Physics-Guided Transformer (PGT): Physics-Aware Attention Mechanism for PINNs
Ehsan Zeraatkar, Rodion Podorozhny, Jelena TeÅ¡iÄ
Reconstructing continuous physical fields from sparse, irregular observations is a central challenge in scientific machine learning, particularly for systems governed by partial di…
Frequency-Aware Vision Transformers for High-Fidelity Super-Resolution of Earth System Models
Ehsan Zeraatkar, Salah A Faroughi, Jelena TeÅ¡iÄ
Super-resolution can play an essential role in enhancing the spatial fidelity of Earth System Model outputs, allowing fine-scale structures highly beneficial to climate science to…
ViSIR: Vision Transformer Single Image Reconstruction Method for Earth System Models
Ehsan Zeraatkar, Salah Faroughi, Jelena TeÅ¡iÄ
Purpose: Earth system models (ESMs) integrate the interactions of the atmosphere, ocean, land, ice, and biosphere to estimate the state of regional and global climate under a wide…
Energy-Efficient Transformer Inference: Optimization Strategies for Time Series Classification
Arshia Kermani, Ehsan Zeraatkar, Habib Irani
The increasing computational demands of transformer models in time series classification necessitate effective optimization strategies for energy-efficient deployment. Our study pr…