8 papers
Building AI-Ready Data Systems for Space Life Sciences, Aerospace Medicine, and Deep Space Exploration
Sylvain V. Costes, Sergio Garcia Busto, Ryan T. Scott +15
While AI holds the potential to revolutionize space life sciences, realizing this promise is contingent upon the systematic restructuring of heterogeneous spaceflight biological da…
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…
KAN KAN Buff Signed Graph Neural Networks?
Muhieddine Shebaro, Jelena TeÅ¡iÄ
Graph Representation Learning aims to create effective embeddings for nodes and edges that encapsulate their features and relationships. Graph Neural Networks (GNNs) leverage neura…
Scaling Frustration Index and Corresponding Balanced State Discovery for Real Signed Graphs
Muhieddine Shebaro, Jelena TeÅ¡iÄ
Structural balance modeling for signed graph networks presents how to model the sources of conflicts. The state-of-the-art focuses on computing the frustration index of a signed gr…