1 code implementation • 8 Aug 2022 • Malachy Moran, Kayla Woputz, Derrick Hee, Manuela Girotto, Paolo D'Odorico, Ritwik Gupta, Daniel Feldman, Puya Vahabi, Alberto Todeschini, Colorado J Reed
Accurately estimating the snowpack in key mountainous basins is critical for water resource managers to make decisions that impact local and global economies, wildlife, and public policy.
1 code implementation • 28 Jul 2022 • Devesh Khandelwal, Sean Campos, Shwetha Nagaraj, Fred Nugen, Alberto Todeschini
In this paper, we demonstrate a unique recipe to enhance the effectiveness of audio machine learning approaches by fusing pre-processing techniques into a deep learning model.
no code implementations • 17 Jan 2022 • Dhileeban Kumaresan, Richard Wang, Ernesto Martinez, Richard Cziva, Alberto Todeschini, Colorado J Reed, Hossein Vahabi
Accurate short-term PV power prediction enables operators to maximize the amount of power obtained from PV panels and safely reduce the reserve energy needed from fossil fuel sources.
1 code implementation • 6 Jan 2022 • Poonam Parhar, Ryan Sawasaki, Alberto Todeschini, Colorado Reed, Hossein Vahabi, Nathan Nusaputra, Felipe Vergara
The energy sector is the single largest contributor to climate change and many efforts are focused on reducing dependence on carbon-emitting power plants and moving to renewable energy sources, such as solar power.
no code implementations • 12 Aug 2021 • Chitra Agastya, Sirak Ghebremusse, Ian Anderson, Colorado Reed, Hossein Vahabi, Alberto Todeschini
Climate change has caused reductions in river runoffs and aquifer recharge resulting in an increasingly unsustainable crop water demand from reduced freshwater availability.
no code implementations • 9 Dec 2020 • Weixin, Wu, Sonal Thakkar, Will Hawkins, Puya Vahabi, Alberto Todeschini
An accurate and precise understanding of global irrigation usage is crucial for a variety of climate science efforts.