3 papers
cs.LG2024
Baseflow identification via explainable AI with Kolmogorov-Arnold networks
Chuyang Liu, Tirthankar Roy, Daniel M. Tartakovsky +1
Hydrological models often involve constitutive laws that may not be optimal in every application. We propose to replace such laws with the Kolmogorov-Arnold networks (KANs), a clas…
cs.LG2024
Reinforcement Learning for Sociohydrology
Tirthankar Roy, Shivendra Srivastava, Beichen Zhang
In this study, we discuss how reinforcement learning (RL) provides an effective and efficient framework for solving sociohydrology problems. The efficacy of RL for these types of p…
cs.LG2024
A Parsimonious Setup for Streamflow Forecasting using CNN-LSTM
Sudan Pokharel, Tirthankar Roy
Significant strides have been made in advancing streamflow predictions, notably with the introduction of cutting-edge machine-learning models. Predominantly, Long Short-Term Memori…