S. Karthik Mukkavilli
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Tackling climate change with machine learning
D Rolnick, PL Donti, LH Kaack, K Kochanski, A Lacoste, K Sankaran, ...
ACM Computing Surveys (CSUR) 55 (2), 1-96, 2022
Drawdown: The most comprehensive plan ever proposed to reverse global warming
P Hawken, C Frischmann, K Wilkinson, R Allard, K Bayuk, JP Gouveia, ...
Penguin, 2017
Assessment of atmospheric aerosols from two reanalysis products over Australia
SK Mukkavilli, AA Prasad, RA Taylor, J Huang, RM Mitchell, A Troccoli, ...
Atmospheric research 215, 149-164, 2019
Visualizing the consequences of climate change using cycle-consistent adversarial networks
V Schmidt, A Luccioni, SK Mukkavilli, N Balasooriya, K Sankaran, ...
International Conference on Learning Representations (ICLR), AI for Social …, 2019
Foundation models for generalist geospatial artificial intelligence
J Jakubik, S Roy, CE Phillips, P Fraccaro, D Godwin, B Zadrozny, ...
arXiv preprint arXiv:2310.18660, 2023
Mesoscale simulations of Australian direct normal irradiance, featuring an extreme dust event
SK Mukkavilli, AA Prasad, RA Taylor, A Troccoli, MJ Kay
Journal of Applied Meteorology and Climatology 57 (3), 493-515, 2018
Strategic foresight to applications of artificial intelligence to achieve water-related sustainable development goals
H Mehmood, SK Mukkavilli, I Weber, A Koshio, C Meechaiya, T Piman, ...
United Nations University Institute for Water, Environment an d Health …, 2020
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation
S Karthik Mukkavilli, D Salles Civitarese, J Schmude, J Jakubik, A Jones, ...
arXiv e-prints, arXiv: 2309.10808, 2023
Deep learning for Aerosol Forecasting
C Hoyne, SK Mukkavilli, D Meger
Neural Information Processing Systems (NeurIPS), Machine Learning and the …, 2019
EnviroNet: ImageNet for Environment
SK Mukkavilli, P Tissot, A Ganguly, L Joppa, D Meger, G Dudek
18th Conference on Artificial and Computational Intelligence and its …, 2019
Lifelines for a Drowning Science‐Improving Findability and Synthesis of Hydrologic Publications
L Stein, SK Mukkavilli, T Wagener
Hydrological Processes, e14742, 2022
Predicting ice flow using machine learning
Y Min, SK Mukkavilli, Y Bengio
Neural Information Processing Systems (NeurIPS), Tackling Climate Change …, 2019
Generative large eddy simulations with conditional variational autoencoders
SK Mukkavilli, MS Pritchard, KG Pressel, G Mooers, PL Ma, S Mandt
AGU Fall Meeting Abstracts 2020, A043-0009, 2020
Climate Change & AI: Present and potential role of AI in assessment and response
L Joppa, V Lakshmanan, V Kumar, G Dudek, SK Mukkavilli, P Tissot
99th American Meteorological Society Annual Meeting, 2019
INDUS: Effective and Efficient Language Models for Scientific Applications
B Bhattacharjee, A Trivedi, M Muraoka, M Ramasubramanian, ...
arXiv preprint arXiv:2405.10725, 2024
Identifying global biases in hydro-hazard research by mining the scientific literature
L Stein, SK Mukkavilli, BM Pfitzmann, PWJ Staar, U Ozturk, C Berrospi, ...
EGU24, 2024
Wealth over Woe: global biases in hydro-hazard research
L Stein, SK Mukkavilli, BM Pfitzmann, PWJ Staar, U Ozturk, C Berrospi, ...
EarthArXiv, 2024
A 3D super-resolution of wind fields via physics-informed pixel-wise self-attention generative adversarial network
T Kurihana, K Yeo, D Szwarcman, B Elmegreen, K Mukkavilli, J Schmude, ...
arXiv preprint arXiv:2312.13212, 2023
TensorBank: Tensor Lakehouse for Foundation Model Training
R Kienzler, J Schmude, N Simumba, B Blumenstiel, M Freitag, D Kimura, ...
2023 IEEE International Conference on Big Data (BigData), 3350-3354, 2023
ClimateHub: Deep Search for Climate, Earth and Environmental Sciences
K Mukkavilli, T Brunschwiler, B Pfitzmann, CB Ramis, A Jones, P Staar
American Geophysical Union Fall Meeting, 2023
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