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AutoML for Climate Change: A Call to Action
Renbo Tu · Nicholas Roberts · Vishak Prasad C · Sibasis Nayak · Paarth Jain · Frederic Sala · Ganesh Ramakrishnan · Ameet Talwalkar · Willie Neiswanger · Colin White

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in Tackling Climate Change with Machine Learning »
Event URL: https://www.climatechange.ai/papers/neurips2022/40 »

The challenge that climate change poses to humanity has spurred a rapidly developing field of artificial intelligence research focused on climate change applications. The climate change ML (CCML) community works on a diverse, challenging set of problems which often involve physics-constrained ML or heterogeneous spatiotemporal data. It would be desirable to use automated machine learning (AutoML) techniques to automatically find high-performing architectures and hyperparameters for a given dataset. In this work, we benchmark popular Auto ML libraries on three high-leverage CCML applications: climate modeling, wind power forecasting, and catalyst discovery. We find that out-of-the-box AutoML libraries currently fail to meaningfully surpass the performance of human-designed CCML models. However, we also identify a few key weaknesses, which stem from the fact that most AutoML techniques are tailored to computer vision and NLP applications. For example, while dozens of search spaces have been designed for image and language data, none have been designed for spatiotemporal data. Addressing these key weaknesses can lead to the discovery of novel architectures that yield substantial performance gains across numerous CCML applications. Therefore, we present a call to action to the AutoML community, since there are a number of concrete, promising directions for future work in the space of AutoML for CCML. We release our code and a list of resources at https://github.com/climate-change-automl/climate-change-automl.

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Author Information

Renbo Tu (University of Toronto)
Nicholas Roberts (University of Wisconsin-Madison)

I am a Ph.D. student in CS at University of Wisconsin – Madison where I am advised by Fred Sala. Before that, I had the pleasure of working with Ameet Talwalkar and Zack Lipton during my MS at Carnegie Mellon University. As an undergraduate, I was extremely fortunate to work with both Sanjoy Dasgupta and Gary Cottrell at the University of California, San Diego. Before that, I was a community college student at Fresno City College, where I was lucky enough to learn calculus, linear algebra, AND C++ from Greg Jamison.

Vishak Prasad C (Indian Institute Of Technology, Bombay)
Sibasis Nayak (Indian Institute of Technology, Bombay)
Paarth Jain (Indian Institute of Technology Bombay)
Frederic Sala (University of Wisconsin, Madison)
Ganesh Ramakrishnan (Indian Institute of Technology Bombay, Indian Institute of Technology Bombay)
Ameet Talwalkar (CMU)
Willie Neiswanger (Carnegie Mellon University)
Colin White (Abacus.AI)

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