Poster Session 2
2022 Poster Session
in
Workshop: Tackling Climate Change with Machine Learning
in
Workshop: Tackling Climate Change with Machine Learning
Abstract
Poster sessions take place in the following Topia space: https://topia.io/neurips-2022-workshop-tccml
The links below provide access to the video presentations, Rocket.chat, direct Topia links and further materials featured on the workshop website.
Papers Track:
- Function Approximations for Reinforcement Learning Controller for Wave Energy Converters
- Bayesian inference for aerosol vertical profiles
- Machine learning emulation of a local-scale UK climate model
- Learning evapotranspiration dataset corrections from water cycle closure supervision
- Optimizing Japanese dam reservoir inflow forecast for efficient operation
- Data-Driven Optimal Solver for Coordinating a Sustainable and Stable Power Grid
- Towards a spatially transferable super resolution model for downscaling Antarctic surface melt
- Exploring Randomly Wired Neural Networks for Climate Model Emulation
- SustainGym: A Benchmark Suite of Reinforcement Learning for Sustainability Applications
- AutoML for Climate Change: A Call to Action
- Reconstruction of Grid Measurements in the Presence of Adversarial Attacks
- Climate Policy Radar: Pipeline for automated analysis of public climate policies
- Controllable Generation for Climate Modeling
- Positional Encoder Graph Neural Networks for Geographic Data
- Image-based Early Detection System for Wildfires
- Pyrocast: a Machine Learning Pipeline to Forecast Pyrocumulonimbus (PyroCb) clouds
- Transformers for Fast Emulation of Atmospheric Chemistry Box Models
- Neural Representation of the Stratospheric Ozone Chemistry
- DL-Corrector-Remapper: A grid-free bias-correction deep learning methodology for data-driven high-resolution global weather forecasting
- An Unsupervised Learning Perspective on the Dynamic Contribution to Extreme Precipitation Changes
- An Interpretable Model of Climate Change Using Correlative Learning
- Multimodal Wildland Fire Smoke Detection
- Accessible Large-Scale Plant Pathology Recognition
- Dynamic weights enabled Physics-Informed Neural Network for simulating the mobility of Engineered Nano Particles in a contaminated aquifer
- Calibration of Large Neural Weather Models
- Learning Surrogates for Diverse Emission Models
Proposals Track:
- Guided Transformer Network for Detecting Methane Emissions in Sentinel-2 Satellite Imagery
- Deep-S2SWind: A data-driven approach for improving Sub-seasonal wind predictions
- Deep learning-based bias adjustment of decadal climate predictions
- Detecting Floods from Cloudy Scenes: A Fusion Approach Using Sentinel-1 and Sentinel-2 Imagery
- Estimating Heating Loads in Alaska using Remote Sensing and Machine Learning Methods
- Interpretable Spatiotemporal Forecasting of Arctic Sea Ice Concentration at Seasonal Lead Times
- Personalizing Sustainable Agriculture with Causal Machine Learning
Tutorials Track:
Chat is not available.
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