Workshop: Tackling Climate Change with Machine Learning
The workshop is part of the Conference on Neural Information Processing Systems (NeurIPS) 2023 in New Orleans, Louisiana, United States. This iteration of the workshop is focused on the theme of blending new and existing knowledge systems to invite and inspire submissions that consider how a machine learning advancement can leverage and integrate existing knowledge. While this theme is broad, and most ML applications to climate change are relevant, the theme is non-binding, and all potential submissions are welcome.
Submit short papers using machine learning to address problems in climate mitigation, adaptation, or modeling, including but not limited to the following topics:
- Agriculture and food
- Behavioural and social science
- Buildings
- Carbon capture and sequestration
- Cities and urban planning
- Climate finance and economics
- Climate justice
- Climate science and climate modeling
- Disaster management and relief
- Earth observations and monitoring
- Earth science
- Ecosystems and biodiversity
- Extreme weather
- Forestry and other land use
- Health
- Heavy industry and manufacturing
- Local and indigenous knowledge systems
- Materials science and discovery
- Oceans and marine systems
- Power and energy systems
- Public policy
- Societal adaptation and resilience
- Supply chains
- Transportation
All machine learning techniques are welcome, from kernel methods to deep learning. Each submission should make clear why the application has (or could have) a pathway to positive impacts regarding climate change. The organisers highly encourage submissions which make their data publicly available. Accepted submissions will be invited to give poster presentations, of which some will be selected for spotlight talks.