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Workshop: Tackling Climate Change with ML

David Dao, Evan Sherwin, Priya Donti, Lauren Kuntz, Lynn Kaack, Yumna Yusuf, David Rolnick, Catherine Nakalembe, Claire Monteleoni, Yoshua Bengio

2020-12-11T03:00:00-08:00 - 2020-12-11T16:00:00-08:00
Abstract: 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.


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2020-12-11T03:00:00-08:00 - 2020-12-11T03:35:00-08:00
Welcome and opening remarks
2020-12-11T03:35:00-08:00 - 2020-12-11T04:00:00-08:00
Keynote by Rose Mwebaza
2020-12-11T04:00:00-08:00 - 2020-12-11T04:05:00-08:00
Introduction to Spotlights
2020-12-11T04:05:00-08:00 - 2020-12-11T04:15:00-08:00
Spotlight: Deep Learning for Climate Model Output Statistics
Michael Steininger
2020-12-11T04:15:00-08:00 - 2020-12-11T04:22:00-08:00
Spotlight: An Enriched Automated PV Registry: Combining Image Recognition and 3D Building Data
Kevin Mayer
2020-12-11T04:22:00-08:00 - 2020-12-11T04:32:00-08:00
Spotlight: Interpretability in Convolutional Neural Networks for Building Damage Classification in Satellite Imagery
Thomas Chen
2020-12-11T04:32:00-08:00 - 2020-12-11T04:42:00-08:00
Spotlight: A Machine Learning Approach to Methane Emissions Mitigation in the Oil and Gas Industry
Jiayang Wang
2020-12-11T04:42:00-08:00 - 2020-12-11T04:52:00-08:00
Spotlight: RainBench: Enabling Data-Driven Precipitation Forecasting on a Global Scale
Catherine Tong
2020-12-11T04:52:00-08:00 - 2020-12-11T05:00:00-08:00
Introduction to first poster session
2020-12-11T05:00:00-08:00 - 2020-12-11T06:00:00-08:00
Poster session 1
2020-12-11T06:00:00-08:00 - 2020-12-11T06:09:00-08:00
Introduction to Spotlights
2020-12-11T06:09:00-08:00 - 2020-12-11T06:19:00-08:00
Spotlight: The Peruvian Amazon Forestry Dataset: A Leaf Image Classification Corpus
Gerson Vizcarra Aguilar
2020-12-11T06:19:00-08:00 - 2020-12-11T06:25:00-08:00
Spotlight: Data-driven modeling of cooling demand in a commercial building
Aqsa Naeem
2020-12-11T06:25:00-08:00 - 2020-12-11T06:37:00-08:00
Spotlight: Structural Forecasting for Tropical Cyclone Intensity Prediction: Providing Insight with Deep Learning
Trey H McNeely
2020-12-11T06:37:00-08:00 - 2020-12-11T06:47:00-08:00
Spotlight: FireSRnet: Geoscience-driven super-resolution of future fire risk from climate change
Tristan Ballard
2020-12-11T06:47:00-08:00 - 2020-12-11T06:57:00-08:00
Spotlight: Spatiotemporal Features Improve Fine-Grained Butterfly Image Classification
Marta Skreta
2020-12-11T07:00:00-08:00 - 2020-12-11T08:00:00-08:00
Climate Change and ML for Policy
Angel Hsu, Dava Newman, James Rattling Leaf, Sr., Mouhamadou M Cisse
2020-12-11T08:00:00-08:00 - 2020-12-11T09:00:00-08:00
Poster session 2
2020-12-11T09:00:00-08:00 - 2020-12-11T09:10:00-08:00
Introduction to Zico Kolter
2020-12-11T09:10:00-08:00 - 2020-12-11T09:40:00-08:00
Keynote by Zico Kolter
J. Zico Kolter
2020-12-11T09:40:00-08:00 - 2020-12-11T10:00:00-08:00
Q&A with Zico Kolter
2020-12-11T10:00:00-08:00 - 2020-12-11T11:00:00-08:00
Climate Change and ML in the Private Sector
Aisha Walcott-Bryant, Lea Boche, Anima Anandkumar
2020-12-11T11:00:00-08:00 - 2020-12-11T11:05:00-08:00
Introduction to Spotlights
2020-12-11T11:05:00-08:00 - 2020-12-11T11:15:00-08:00
Spotlight: Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya
Kris Sankaran
2020-12-11T11:15:00-08:00 - 2020-12-11T11:25:00-08:00
Spotlight: Wildfire Smoke and Air Quality: How Machine Learning Can Guide Forest Management
Lorenzo Tomaselli
2020-12-11T11:25:00-08:00 - 2020-12-11T11:36:00-08:00
Spotlight: OGNet: Towards a Global Oil and Gas Infrastructure Database using Deep Learning on Remotely Sensed Imagery
Hao Sheng
2020-12-11T11:36:00-08:00 - 2020-12-11T11:45:00-08:00
Spotlight: Climate Change Driven Crop Yield Failures
Somya Sharma
2020-12-11T11:45:00-08:00 - 2020-12-11T11:55:00-08:00
Spotlight: Towards Tracking the Emissions of Every Power Plant on the Planet
Heather Couture
2020-12-11T12:00:00-08:00 - 2020-12-11T13:00:00-08:00
Poster session 3
2020-12-11T13:00:00-08:00 - 2020-12-11T13:10:00-08:00
Introduction to Jennifer Chayes
2020-12-11T13:10:00-08:00 - 2020-12-11T13:40:00-08:00
Keynote by Jennifer Chayes
Jennifer Chayes
2020-12-11T13:40:00-08:00 - 2020-12-11T14:00:00-08:00
Q&A with Jennifer Chayes
2020-12-11T14:00:00-08:00 - 2020-12-11T14:50:00-08:00
Fireside Chat with Vinod Khosla
Vinod Khosla
2020-12-11T14:50:00-08:00 - 2020-12-11T15:15:00-08:00
Closing remarks
2020-12-11T15:15:00-08:00 - 2020-12-11T16:00:00-08:00
Poster reception
DeepWaste: Applying Deep Learning to Waste Classification for a Sustainable Planet
Yash Narayan
Monitoring the Impact of Wildfires on Tree Species with Deep Learning
Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models
Eric Zelikman
Artificial Intelligence, Machine Learning and Modeling for Understanding the Oceans and Climate Change
Luis Martí
Deep learning architectures for inference of AC-OPF solutions
Thomas Falconer
Short-term prediction of photovoltaic power generation using Gaussian process regression
Yahya Al Lawati
Movement Tracks for the Automatic Detection of Fish Behavior in Videos
Declan GD McIntosh
Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery
Issam Hadj Laradji
EarthNet2021: A novel large-scale dataset and challenge for forecasting localized climate impacts
Christian Requena-Mesa
Characterization of Industrial Smoke Plumes from Remote Sensing Data
Michael Mommert
Quantifying the presence of air pollutants over a road network in high spatio-temporal resolution
Matteo Bohm
Optimal District Heating in China with Deep Reinforcement Learning
Adrien Le Coz
Can Federated Learning Save The Planet ?
Xinchi Qiu
A Comparison of Data-Driven Models for Predicting Stream Water Temperature
Helen Weierbach
Machine Learning towards a Global Parametrization of Atmospheric New Particle Formation and Growth
Mihalis Nicolaou
Analyzing Sustainability Reports Using Natural Language Processing
Sasha Luccioni
High-resolution global irrigation prediction with Sentinel-2 30m data
Will Hawkins
pymgrid: An Open-Source Python Microgrid Simulator for Applied Artificial Intelligence Research
Gonzague Henri
A Temporally Consistent Image-based Sun Tracking Algorithm for Solar Energy Forecasting Applications
Quentin Paletta
Investigating two super-resolution methods for downscaling precipitation: ESRGAN and CAR
Campbell Watson
Explaining Complex Energy Systems: A Challenge
Jonas Hülsmann
HECT: High-Dimensional Ensemble Consistency Testing for Climate Models
Nic Dalmasso
ACED: Accelerated Computational Electrochemical systems Discovery
Rachel C Kurchin
Machine learning for advanced solar cell production: adversarial denoising, sub-pixel alignment and the digital twin
Matthias Demant
ClimaText: A Dataset for Climate Change Topic Detection
Markus Leippold
Estimating Forest Ground Vegetation Cover From Nadir Photographs Using Deep Convolutional Neural Networks
Martin Barczyk
Graph Neural Networks for Improved El Niño Forecasting
Salva Rühling Cachay
Hyperspectral Remote Sensing of Aquatic Microbes to Support Water Resource Management
Grace Kim
Long-Range Seasonal Forecasting of 2m-Temperature with Machine Learning
Etienne Vos
Short-term PV output prediction using convolutional neural network: learning from an imbalanced sky images dataset via sampling and data augmentation
Yuhao Nie
Loosely Conditioned Emulation of Global Climate Models With Generative Adversarial Networks
Brian Hutchinson
Annual and in-season mapping of cropland at field scale with sparse labels
Gabriel Tseng
ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery
Jeremy Irvin
Forecasting Marginal Emissions Factors in PJM
Amy Wang
Is Africa leapfrogging to renewables or heading for carbon lock-in? A machine-learning-based approach to predicting success of power-generation projects
Galina Alova
Monitoring Shorelines via High-Resolution Satellite Imagery and Deep Learning
Venkatesh Ramesh
Do Occupants in a Building exhibit patterns in Energy Consumption? Analyzing Clusters in Energy Social Games
Hari Prasanna Das
Privacy Preserving Demand Forecasting to Encourage Consumer Acceptance of Smart Energy Meters
Chris Briggs
Towards Data-Driven Physics-Informed Global Precipitation Forecasting from Satellite Imagery
Valentina Zantedeschi
Learning the distribution of extreme precipitation from atmospheric general circulation model variables
Philipp Hess
NightVision: Generating Nighttime Satellite Imagery from Infra-Red Observations
Paula Harder
A Way Toward Low-Carbon Shipping: Improving Port Operations Planning using Machine Learning
Sara El Mekkaoui
Electric Vehicle Range Improvement by Utilizing Deep Learning to Optimize Occupant Thermal Comfort
Alok Warey
Climate-FEVER: A Dataset for Verification of Real-World Climate Claims
Markus Leippold
Residue Density Segmentation for Monitoring and Optimizing Tillage Practices
Jennifer Hobbs
Towards DeepSentinel: An extensible corpus of labelled Sentinel-1 and -2 imagery and a proposed general purpose sensor-fusion semantic embedding model
Lucas Kruitwagen
Machine Learning Climate Model Dynamics: Offline versus Online Performance
Noah Brenowitz
Spatio-Temporal Learning for Feature Extraction inTime-Series Images
Gael Kamdem De Teyou
Understanding global fire regimes using Artificial Intelligence
Cristobal Pais
Mangrove Ecosystem Detection using Mixed-Resolution Imagery with a Hybrid-Convolutional Neural Network
Dillon Hicks
Deep Fire Topology: Understanding the role of landscape spatial patterns in wildfire susceptibility
Cristobal Pais
Street to Cloud: Improving Flood Maps With Crowdsourcing and Semantic Segmentation
Veda Sunkara
Leveraging Machine learning for Sustainable and Self-sufficient Energy Communities
Anthony Faustine
Storing Energy with Organic Molecules: Towards a Metric for Improving Molecular Performance for Redox Flow Batteries
Luis Martin Mejia Mendoza
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
Robbie Jones
A Multi-source, End-to-End Solution for Tracking Climate Change Adaptation in Agriculture
Alejandro Coca-Castro
Formatting the Landscape: Spatial conditional GAN for varying population in satellite imagery
Tomas Langer
Meta-modeling strategy for data-driven forecasting
Dominic Skinner
Predicting the Solar Potential of Rooftops using Image Segmentation and Structured Data
Daniel de Barros Soares
Accurate river level predictions using a Wavenet-like model
Shannon Doyle
Using attention to model long-term dependencies in occupancy behavior
Max Kleinebrahm
Satellite imagery analysis for Land Use, Land Use Change and Forestry: A pilot study in Kigali, Rwanda
Bright Aboh
Narratives and Needs: Analyzing Experiences of Cyclone Amphan Using Twitter Discourse
Ancil Crayton
Quantitative Assessment of Drought Impacts Using XGBoost based on the Drought Impact Reporter
Beichen Zhang
Predicting Landsat Reflectance with Deep Generative Fusion
Shahine Bouabid
FlowDB: A new large scale river flow, flash flood, and precipitation dataset
Isaac Godfried
Machine Learning Informed Policy for Environmental Justice in Atlanta with Climate Justice Implications
Lelia Hampton
VConstruct: Filling Gaps in Chl-a Data Using a Variational Autoencoder
Matthew Ehrler
The Human Effect Requires Affect: Addressing Social-Psychological Factors of Climate Change with Machine Learning
Kyle Tilbury
Revealing the Oil Majors' Adaptive Capacity to the Energy Transition with Deep Multi-Agent Reinforcement Learning
Dylan Radovic
Expert-in-the-loop Systems Towards Safety-critical Machine Learning Technology in Wildfire Intelligence
Maria João Sousa
Automated Salmonid Counting in Sonar Data
Peter Kulits
A Generative Adversarial Gated Recurrent Network for Power Disaggregation & Consumption Awareness
Maria Kaselimi
OfficeLearn: An OpenAI Gym Environment for Building Level Energy Demand Response
Lucas Spangher
Physics-constrained Deep Recurrent Neural Models of Building Thermal Dynamics
Jan Drgona
Emerging Trends of Sustainability Reporting in the ICT Industry: Insights from Discriminative Topic Mining
Lin Shi
Context-Aware Urban Energy Efficiency Optimization Using Hybrid Physical Models
Ben Choi
Deep Reinforcement Learning in Electricity Generation Investment for the Minimization of Long-Term Carbon Emissions and Electricity Costs
Alex Kell
Automated Identification of Oil Field Features using CNNs