Climate change is one of the greatest problems society has ever faced, with increasingly severe consequences for humanity as natural disasters multiply, sea levels rise, and ecosystems falter. Since climate change is a complex issue, action takes many forms, from designing smart electric grids to tracking greenhouse gas emissions through satellite imagery. While no silver bullet, machine learning can be an invaluable tool in fighting climate change via a wide array of applications and techniques. These applications require algorithmic innovations in machine learning and close collaboration with diverse fields and practitioners. This workshop is intended as a forum for those in the machine learning community who wish to help tackle climate change. Building on our past workshops on this topic, this workshop aims to especially emphasize the pipeline to impact, through conversations about machine learning with decision-makers and other global leaders in implementing climate change strategies. The all-virtual format of NeurIPS 2020 provides a special opportunity to foster cross-pollination between researchers in machine learning and experts in complementary fields.
| Welcome and opening remarks (Introductory remarks) | |
| Introduction to Spotlights (Live introduction) | |
| Spotlight: Deep Learning for Climate Model Output Statistics (Spotlight talk) | |
| Spotlight: An Enriched Automated PV Registry: Combining Image Recognition and 3D Building Data (Spotlight talk) | |
| Spotlight: Interpretability in Convolutional Neural Networks for Building Damage Classification in Satellite Imagery (Spotlight talk) | |
| Spotlight: A Machine Learning Approach to Methane Emissions Mitigation in the Oil and Gas Industry (Spotlight talk) | |
| Spotlight: RainBench: Enabling Data-Driven Precipitation Forecasting on a Global Scale (Spotlight talk) | |
| Introduction to first poster session (Live introduction) | |
| Poster session 1 (Poster session) | |
| Introduction to Spotlights (Live introduction) | |
| Spotlight: The Peruvian Amazon Forestry Dataset: A Leaf Image Classification Corpus (Spotlight talk) | |
| Spotlight: Data-driven modeling of cooling demand in a commercial building (Spotlight talk) | |
| Spotlight: Structural Forecasting for Tropical Cyclone Intensity Prediction: Providing Insight with Deep Learning (Spotlight talk) | |
| Spotlight: FireSRnet: Geoscience-driven super-resolution of future fire risk from climate change (Spotlight talk) | |
| Spotlight: Spatiotemporal Features Improve Fine-Grained Butterfly Image Classification (Spotlight talk) | |
| Climate Change and ML for Policy (Discussion Panel) | |
| Poster session 2 (Poster session) | |
| Introduction to Zico Kolter (Live introduction) | |
| Q&A with Zico Kolter (Live Q&A) | |
| Climate Change and ML in the Private Sector (Discussion Panel) | |
| Introduction to Spotlights (Live introduction) | |
| Spotlight: Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya (Spotlight talk) | |
| Spotlight: Wildfire Smoke and Air Quality: How Machine Learning Can Guide Forest Management (Spotlight talk) | |
| Spotlight: OGNet: Towards a Global Oil and Gas Infrastructure Database using Deep Learning on Remotely Sensed Imagery (Spotlight talk) | |
| Spotlight: Climate Change Driven Crop Yield Failures (Spotlight talk) | |
| Spotlight: Towards Tracking the Emissions of Every Power Plant on the Planet (Spotlight talk) | |
| Poster session 3 (Poster session) | |
| Introduction to Jennifer Chayes (Live introduction) | |
| Q&A with Jennifer Chayes (Live Q&A) | |
| Closing remarks | |
| Poster reception (Poster session) | |
| Automated Salmonid Counting in Sonar Data (Poster) | |
| ACED: Accelerated Computational Electrochemical systems Discovery (Poster) | |
| Forecasting Marginal Emissions Factors in PJM (Poster) | |
| Short-term PV output prediction using convolutional neural network: learning from an imbalanced sky images dataset via sampling and data augmentation (Poster) | |
| Investigating two super-resolution methods for downscaling precipitation: ESRGAN and CAR (Poster) | |
| Emerging Trends of Sustainability Reporting in the ICT Industry: Insights from Discriminative Topic Mining (Poster) | |
| Loosely Conditioned Emulation of Global Climate Models With Generative Adversarial Networks (Poster) | |
| High-resolution global irrigation prediction with Sentinel-2 30m data (Poster) | |
| In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness (Poster) | |
| Understanding global fire regimes using Artificial Intelligence (Poster) | |
| ClimaText: A Dataset for Climate Change Topic Detection (Poster) | |
| Towards Data-Driven Physics-Informed Global Precipitation Forecasting from Satellite Imagery (Poster) | |
| Long-Range Seasonal Forecasting of 2m-Temperature with Machine Learning (Poster) | |
| Formatting the Landscape: Spatial conditional GAN for varying population in satellite imagery (Poster) | |
| Predicting Landsat Reflectance with Deep Generative Fusion (Poster) | |
| Quantitative Assessment of Drought Impacts Using XGBoost based on the Drought Impact Reporter (Poster) | |
| HECT: High-Dimensional Ensemble Consistency Testing for Climate Models (Poster) | |
| Mangrove Ecosystem Detection using Mixed-Resolution Imagery with a Hybrid-Convolutional Neural Network (Poster) | |
| Quantifying the presence of air pollutants over a road network in high spatio-temporal resolution (Poster) | |
| Analyzing Sustainability Reports Using Natural Language Processing (Poster) | |
| Street to Cloud: Improving Flood Maps With Crowdsourcing and Semantic Segmentation (Poster) | |
| Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery (Poster) | |
| EarthNet2021: A novel large-scale dataset and challenge for forecasting localized climate impacts (Poster) | |
| Expert-in-the-loop Systems Towards Safety-critical Machine Learning Technology in Wildfire Intelligence (Poster) | |
| Electric Vehicle Range Improvement by Utilizing Deep Learning to Optimize Occupant Thermal Comfort (Poster) | |
| Explaining Complex Energy Systems: A Challenge (Poster) | |
| Is Africa leapfrogging to renewables or heading for carbon lock-in? A machine-learning-based approach to predicting success of power-generation projects (Poster) | |
| pymgrid: An Open-Source Python Microgrid Simulator for Applied Artificial Intelligence Research (Poster) | |
| Deep Reinforcement Learning in Electricity Generation Investment for the Minimization of Long-Term Carbon Emissions and Electricity Costs (Poster) | |
| Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models (Poster) | |
| Learning the distribution of extreme precipitation from atmospheric general circulation model variables (Poster) | |
| The Human Effect Requires Affect: Addressing Social-Psychological Factors of Climate Change with Machine Learning (Poster) | |
| Spatio-Temporal Learning for Feature Extraction inTime-Series Images (Poster) | |
| Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters (Poster) | |
| Towards DeepSentinel: An extensible corpus of labelled Sentinel-1 and -2 imagery and a proposed general purpose sensor-fusion semantic embedding model (Poster) | |
| Annual and in-season mapping of cropland at field scale with sparse labels (Poster) | |
| Automated Identification of Oil Field Features using CNNs (Poster) | |
| Machine Learning Informed Policy for Environmental Justice in Atlanta with Climate Justice Implications (Poster) | |
| Narratives and Needs: Analyzing Experiences of Cyclone Amphan Using Twitter Discourse (Poster) | |
| A Multi-source, End-to-End Solution for Tracking Climate Change Adaptation in Agriculture (Poster) | |
| OfficeLearn: An OpenAI Gym Environment for Building Level Energy Demand Response (Poster) | |
| Do Occupants in a Building exhibit patterns in Energy Consumption? Analyzing Clusters in Energy Social Games (Poster) | |
| Machine Learning towards a Global Parametrization of Atmospheric New Particle Formation and Growth (Poster) | |
| Artificial Intelligence, Machine Learning and Modeling for Understanding the Oceans and Climate Change (Poster) | |
| Monitoring Shorelines via High-Resolution Satellite Imagery and Deep Learning (Poster) | |
| Meta-modeling strategy for data-driven forecasting (Poster) | |
| A Way Toward Low-Carbon Shipping: Improving Port Operations Planning using Machine Learning (Poster) | |
| Residue Density Segmentation for Monitoring and Optimizing Tillage Practices (Poster) | |
| A Generative Adversarial Gated Recurrent Network for Power Disaggregation & Consumption Awareness (Poster) | |
| Optimal District Heating in China with Deep Reinforcement Learning (Poster) | |
| A Temporally Consistent Image-based Sun Tracking Algorithm for Solar Energy Forecasting Applications (Poster) | |
| Characterization of Industrial Smoke Plumes from Remote Sensing Data (Poster) | |
| Short-term prediction of photovoltaic power generation using Gaussian process regression (Poster) | |
| Leveraging Machine learning for Sustainable and Self-sufficient Energy Communities (Poster) | |
| Storing Energy with Organic Molecules: Towards a Metric for Improving Molecular Performance for Redox Flow Batteries (Poster) | |
| Estimating Forest Ground Vegetation Cover From Nadir Photographs Using Deep Convolutional Neural Networks (Poster) | |
| Hyperspectral Remote Sensing of Aquatic Microbes to Support Water Resource Management (Poster) | |
| Monitoring the Impact of Wildfires on Tree Species with Deep Learning (Poster) | |
| ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery (Poster) | |
| Context-Aware Urban Energy Efficiency Optimization Using Hybrid Physical Models (Poster) | |
| Deep learning architectures for inference of AC-OPF solutions (Poster) | |
| Predicting the Solar Potential of Rooftops using Image Segmentation and Structured Data (Poster) | |
| Revealing the Oil Majors' Adaptive Capacity to the Energy Transition with Deep Multi-Agent Reinforcement Learning (Poster) | |
| NightVision: Generating Nighttime Satellite Imagery from Infra-Red Observations (Poster) | |
| Using attention to model long-term dependencies in occupancy behavior (Poster) | |
| Accurate river level predictions using a Wavenet-like model (Poster) | |
| Graph Neural Networks for Improved El Niño Forecasting (Poster) | |
| Movement Tracks for the Automatic Detection of Fish Behavior in Videos (Poster) | |
| Machine learning for advanced solar cell production: adversarial denoising, sub-pixel alignment and the digital twin (Poster) | |
| Physics-constrained Deep Recurrent Neural Models of Building Thermal Dynamics (Poster) | |
| Deep Fire Topology: Understanding the role of landscape spatial patterns in wildfire susceptibility (Poster) | |
| FlowDB: A new large scale river flow, flash flood, and precipitation dataset (Poster) | |
| Can Federated Learning Save The Planet ? (Poster) | |
| Satellite imagery analysis for Land Use, Land Use Change and Forestry: A pilot study in Kigali, Rwanda (Poster) | |
| DeepWaste: Applying Deep Learning to Waste Classification for a Sustainable Planet (Poster) | |
| Machine Learning Climate Model Dynamics: Offline versus Online Performance (Poster) | |
| VConstruct: Filling Gaps in Chl-a Data Using a Variational Autoencoder (Poster) | |
| A Comparison of Data-Driven Models for Predicting Stream Water Temperature (Poster) | |
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