Publications

Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology

Published in KDD 22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022

In this paper, we propose a novel Knowledge-guided Self-Supervised Learning (KGSSL) inverse framework to extract system characteristics from driver(input) and response(output) data

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Regionalization in a global hydrologic deep learning model: From physical descriptors to random vectors

Published in Water Resources Research, 2022

In this paper, we show that by assigning a vector of random values as a surrogate for catchment physical descriptors, we can achieve robust regionalization performance under a gauged prediction scenario

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Arvind Renganathan

Publications

Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology

Regionalization in a global hydrologic deep learning model: From physical descriptors to random vectors