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The 2021 schedule is still incomplete
Fri Jul 23 05:00 AM -- 05:00 PM (PDT)
Tackling Climate Change with Machine Learning
Hari Prasanna Das · Katarzyna Tokarska · Maria João Sousa · Meareg Hailemariam · David Rolnick · Xiaoxiang Zhu · Yoshua Bengio

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The focus of this workshop is on the use of machine learning to help in addressing climate change, encompassing mitigation efforts (reducing the severity of climate change), adaptation measures (preparing for unavoidable consequences), and climate science (our understanding of the climate and future climate predictions). Topics within the scope of this workshop include 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 demonstrate that the associated ML methods are interesting in their own right, (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, ensuring that the works presented in this workshop have impact on the thoughtful deployment of ML in climate solutions. Building on our previous workshops in this series, this workshop will have a particular focus on ML for the assessment and implementation of objectives set under the Paris Agreement, though submitted works may be on any topic at the intersection of ML and climate change.

Opening Remarks
Solomon Assefa: Addressing Enterprise Decarbonization and Climate Resiliency Goals with Advances in AI, Cloud, and Quantum Computing (Keynote Talk)
Physics-Informed Graph Neural Networks for Robust Fault Location in Power Grids (Spotlight Talk)
From Talk to Action with Accountability: Monitoring the Public Discussion of Policy Makers with Deep Neural Networks and Topic Modelling (Spotlight Talk)
Toward efficient calibration of higher-resolution Earth System Models (Spotlight Talk)
Panel Discussion: Designing Projects and Finding Collaborators in Climate Change and ML (Panel)
Poster Session 1 (Poster Session)
Harnessing Machine Learning to Achieve Net Zero (Keynote Talk)
Reinforcement Learning for Optimal Frequency Control: A Lyapunov Approach (Spotlight Talk)
NeuralNERE: Neural Named Entity Relationship Extraction for End-to-End Climate Change Knowledge Graph Construction (Spotlight Talk)
An Accurate and Scalable Subseasonal Forecasting Toolkit for the United States (Spotlight Talk)
Extreme Precipitation Seasonal Forecast Using a Transformer Neural Network (Spotlight Talk)
Wildfire Smoke Plume Segmentation Using Geostationary Satellite Imagery (Spotlight Talk)
Panel Discussion: Monitoring and Mitigation of Emissions in Line with Paris Agreement Targets (Panel)
Poster Session 2 (Poster Session)
Kate Marvel: Using Machine Learning to Understand Present and Future Climate Changes: an Invitation (Keynote Talk)
Enhancing Laboratory-scale Flow Imaging of Fractured Geological Media with Deep Learning Super Resolution (Spotlight Talk)
On the Role of Spatial Clustering Algorithms in Building Species Distribution Models from Community Science Data (Spotlight Talk)
Revealing the impact of global warming on climate modes using transparent machine learning and a suite of climate models (Spotlight Talk)
Tackling the Overestimation of Forest Carbon with Deep Learning and Aerial Imagery (Spotlight Talk)
Designing Bounded min-knapsack Bandits algorithm for Sustainable Demand Response (Spotlight Talk)
Draguna Vrabie: Differentiable Predictive Control (Keynote Talk)
Closing Remarks and Awards (Closing Remarks)
Poster Session 3 (Poster Session)
Gather.town networking (Networking Session)