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cs.LG2024
Hybrid variable spiking graph neural networks for energy-efficient scientific machine learning
Isha Jain, Shailesh Garg, Shaurya Shriyam +1
Graph-based representations for samples of computational mechanics-related datasets can prove instrumental when dealing with problems like irregular domains or molecular structures…
stat.ML2024
Distribution free uncertainty quantification in neuroscience-inspired deep operators
Shailesh Garg, Souvik Chakraborty
Energy-efficient deep learning algorithms are essential for a sustainable future and feasible edge computing setups. Spiking neural networks (SNNs), inspired from neuroscience, are…