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25 papers · 1 filter
PyGALAX: An Open-Source Python Toolkit for Advanced Explainable Geospatial Machine Learning
Pingping Wang, Yihong Yuan, Lingcheng Li +1
PyGALAX is a Python package for geospatial analysis that integrates automated machine learning (AutoML) and explainable artificial intelligence (XAI) techniques to analyze spatial…
Knowledge Homophily in Large Language Models
Utkarsh Sahu, Zhisheng Qi, Mahantesh Halappanavar +6
Large Language Models (LLMs) have been increasingly studied as neural knowledge bases for supporting knowledge-intensive applications such as question answering and fact checking.…
Sim-to-real supervised domain adaptation for radioisotope identification
Peter Lalor, Henry Adams, Alex Hagen
Machine learning has the potential to improve the speed and reliability of radioisotope identification using gamma spectroscopy. However, meticulously labeling an experimental data…
Self-adaptive weights based on balanced residual decay rate for physics-informed neural networks and deep operator networks
Wenqian Chen, Amanda A. Howard, Panos Stinis
Physics-informed deep learning has emerged as a promising alternative for solving partial differential equations. However, for complex problems, training these networks can still b…
Scientific Computing Algorithms to Learn Enhanced Scalable Surrogates for Mesh Physics
Brian R. Bartoldson, Yeping Hu, Amar Saini +6
Data-driven modeling approaches can produce fast surrogates to study large-scale physics problems. Among them, graph neural networks (GNNs) that operate on mesh-based data are desi…
A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining
Hongwu Peng, Shaoyi Huang, Shiyang Chen +8
Transformers are considered one of the most important deep learning models since 2018, in part because it establishes state-of-the-art (SOTA) records and could potentially replace…