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Tue Dec 14 06:15 AM -- 05:00 PM (PST)
Tackling Climate Change with Machine Learning
Maria João Sousa · Hari Prasanna Das · Sally Simone Fobi · Jan Drgona · Tegan Maharaj · Yoshua Bengio

The focus of this workshop is the use of machine learning to help address climate change, encompassing mitigation efforts (reducing greenhouse gas emissions), adaptation measures (preparing for unavoidable consequences), and climate science (our understanding of the climate and future climate predictions). The scope of the workshop includes climate-relevant applications of machine learning to the power sector, buildings and transportation infrastructure, agriculture and land use, extreme event prediction, disaster response, climate policy, and climate finance. The goals of the workshop are: (1) to showcase high-impact applications of ML to climate change mitigation, adaptation, and climate science, (2) to showcase novel and interesting problem settings and challenges for ML techniques, (3) to encourage fruitful collaboration between the ML community and a diverse set of researchers and practitioners from climate change-related fields, and (4) to promote dialogue with decision-makers in the private and public sectors to ensure that the work presented leads to responsible and meaningful deployment.

Opening Remarks
Daron Acemoglu: Is AI the Solution to Climate Change? (Keynote talk)
Resolving Super Fine-Resolution SIF via Coarsely-Supervised U-Net Regression (Spotlight)
Detecting Abandoned Oil Wells Using Machine Learning and Semantic Segmentation (Spotlight)
Semi-Supervised Classification and Segmentation on High Resolution Aerial Images (Spotlight)
A GNN-RNN Approach for Harnessing Geospatial and Temporal Information: Application to Crop Yield Prediction (Spotlight)
Poster Session 1 (Poster Session)
Discussion Panel 1: Decision Making (Discussion Panel)
Two-phase training mitigates class imbalance for camera trap image classification with CNNs (Spotlight)
Predicting Atlantic Multidecadal Variability (Spotlight)
Learned Benchmarks for Subseasonal Forecasting (Spotlight)
Anima Anandkumar: Role of AI in predicting and mitigating climate change (Keynote talk)
ClimART: A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models (Spotlight)
DeepQuake: Artificial Intelligence for Earthquake Forecasting Using Fine-Grained Climate Data (Spotlight)
Hurricane Forecasting: A Novel Multimodal Machine Learning Framework (Spotlight)
Emissions-aware electricity network expansion planning via implicit differentiation (Spotlight)
Tianzhen Hong: Machine Learning for Smart Buildings: Applications and Perspectives (Keynote talk)
Poster Session 2 (Poster Session)
Discussion Panel: Data (Discussion Panel)
Tutorials track intro (Track intro)
A day in a sustainable life (Tutorial)
Open Catalyst Project: An Introduction to ML applied to Molecular Simulations (Tutorial)
Amy McGovern: Developing Trustworthy AI for Weather and Climate (Keynote talk)
Closing remarks and awards (Closing remarks)
Poster Session 3 (Poster Session)
Gather.Town networking (Networking)