Poster Session
Workshop: Tackling Climate Change with Machine Learning

Poster Session 1


Poster sessions take place in the following Topia space:

The links below provide access to the video presentations,, direct Topia links and further materials featured on the workshop website.

Papers Track:

  1. Function Approximations for Reinforcement Learning Controller for Wave Energy Converters
  2. Image-Based Soil Organic Carbon Estimation from Multispectral Satellite Images with Fourier Neural Operator and Structural Similarity
  3. SolarDK: A high-resolution urban solar panel image classification and localisation dataset
  4. Optimizing toward efficiency for SAR image ship detection
  5. AutoML-based Almond Yield Prediction and Projection in California
  6. Attention-Based Scattering Network for Satellite Imagery
  7. Aboveground carbon biomass estimate with Physics-informed deep network
  8. Improving the predictions of ML-corrected climate models with novelty detection
  9. Scene-to-Patch Earth Observation: Multiple Instance Learning for Land Cover Classification
  10. Deep learning for downscaling tropical cyclone rainfall
  11. Short-term Prediction and Filtering of Solar Power Using State-Space Gaussian Processes
  12. Identifying latent climate signals using sparse hierarchical Gaussian processes
  13. Towards dynamical stability analysis of sustainable power grids using Graph Neural Networks
  14. Detecting Methane Plumes using PRISMA: Deep Learning Model and Data Augmentation
  15. Probabilistic forecasting of regional photovoltaic power production based on satellite-derived cloud motion
  16. Robustifying machine-learned algorithms for efficient grid operation
  17. Deep Hydrology: Hourly, Gap-Free Flood Maps Through Joint Satellite and Hydrologic Modelling
  18. Convolutional Neural Processes for Inpainting Satellite Images: Application to Water Body Segmentation
  19. A POMDP Model for Safe Geological Carbon Sequestration
  20. Deep Climate Change: A Dataset and Adaptive domain pre-trained Language Models for Climate Change Related Tasks
  21. Data-Driven Optimal Solver for Coordinating a Sustainable and Stable Power Grid
  22. Don't Waste Data: Transfer Learning to Leverage All Data for Machine-Learnt Climate Model Emulation
  23. Explainable Multi-Agent Recommendation System for Energy-Efficient Decision Support in Smart Homes
  24. FIRO: A Deep-neural Network for Wildfire Forecast with Interpretable Hidden States
  25. Towards a spatially transferable super resolution model for downscaling Antarctic surface melt
  26. Forecasting European Ozone Air Pollution With Transformers
  27. Stability Constrained Reinforcement Learning for Real-Time Voltage Control
  28. Land Use Prediction using Electro-Optical to SAR Few-Shot Transfer Learning
  29. Exploring Randomly Wired Neural Networks for Climate Model Emulation
  30. SustainGym: A Benchmark Suite of Reinforcement Learning for Sustainability Applications
  31. Remote estimation of geologic composition using interferometric synthetic-aperture radar in California’s Central Valley
  32. Temperature impacts on hate speech online: evidence from four billion tweets
  33. Cross Modal Distillation for Flood Extent Mapping
  34. Transformer Neural Networks for Building Load Forecasting
  35. Estimating Chicago’s tree cover and canopy height using multi-spectral satellite imagery
  36. Reconstruction of Grid Measurements in the Presence of Adversarial Attacks
  37. Heat Demand Forecasting with Multi-Resolutional Representation of Heterogeneous Temporal Ensemble
  38. Identifying Compound Climate Drivers of Forest Mortality with β-VAE
  39. TCFD-NLP: Assessing alignment of climate disclosures using NLP for the financial markets
  40. Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes
  41. Hybrid Recurrent Neural Network for Drought Monitoring
  42. Deep Learning for Global Wildfire Forecasting
  43. Causal Modeling of Soil Processes for Improved Generalization
  44. Machine Learning for Activity-Based Road Transportation Emissions Estimation
  45. Estimating Corporate Scope 1 Emissions Using Tree-Based Machine Learning Methods
  46. Analyzing Micro-Level Rebound Effects of Energy Efficient Technologies
  47. Comparing the carbon costs and benefits of low-resource solar nowcasting
  48. Climate Policy Radar: Pipeline for automated analysis of public climate policies
  49. Inferring signatures of reinforcing ideology underlying carbon tax opposition
  50. Curriculum Based Reinforcement Learning to Avert Cascading Failures in the Electric Grid
  51. Short-range forecasts of global precipitation using deep learning-augmented numerical weather prediction
  52. A Multi-Scale Deep Learning Framework for Projecting Weather Extremes
  53. A Global Classification Model for Cities using ML
  54. EnhancedSD: Predicting Solar Power Reanalysis from Climate Projections via Image Super-Resolution
  55. Positional Encoder Graph Neural Networks for Geographic Data
  56. Towards Global Crop Maps with Transfer Learning
  57. Pyrocast: a Machine Learning Pipeline to Forecast Pyrocumulonimbus (PyroCb) clouds
  58. Evaluating Digital Tools for Sustainable Agriculture using Causal Inference
  59. Generating physically-consistent high-resolution climate data with hard-constrained neural networks
  60. Flood Prediction with Graph Neural Networks
  61. Neural Representation of the Stratospheric Ozone Chemistry
  62. Industry-scale CO2 Flow Simulations with Model-Parallel Fourier Neural Operators
  63. Adaptive Bias Correction for Improved Subseasonal Forecast
  64. An Interpretable Model of Climate Change Using Correlative Learning
  65. Multimodal Wildland Fire Smoke Detection
  66. Using uncertainty-aware machine learning models to study aerosol-cloud interactions
  67. Accessible Large-Scale Plant Pathology Recognition
  68. Dynamic weights enabled Physics-Informed Neural Network for simulating the mobility of Engineered Nano Particles in a contaminated aquifer
  69. Learning to forecast vegetation greenness at fine resolution over Africa with ConvLSTMs
  70. Generative Modeling of High-resolution Global Precipitation Forecasts
  71. Continual VQA for Disaster Response Systems
  72. Performance evaluation of deep segmentation models on Landsat-8 imagery

Proposals Track:

  • Guided Transformer Network for Detecting Methane Emissions in Sentinel-2 Satellite Imagery
  • Identification of medical devices using machine learning on distribution feeder data for informing power outage response
  • Analyzing the global energy discourse with machine learning
  • Towards Low Cost Automated Monitoring of Life Below Water to De-risk Ocean-Based Carbon Dioxide Removal and Clean Power
  • Towards the Automatic Analysis of Ceilometer Backscattering Profiles using Unsupervised Learning
  • Modelling the performance of delivery vehicles across urban micro-regions to accelerate the transition to cargo-bike logistics
  • An Inversion Algorithm of Ice Thickness and InSAR Data for the State of Friction at the Base of the Greenland Ice Sheet
  • Deep learning-based bias adjustment of decadal climate predictions
  • Surrogate Modeling for Methane Dispersion Simulations Using Fourier Neural Operator
  • Urban Heat Island Detection and Causal Inference Using Convolutional Neural Networks
  • Forecasting Global Drought Severity and Duration Using Deep Learning
  • ForestBench: Equitable Benchmarks for Monitoring, Reporting, and Verification of Nature-Based Solutions with Machine Learning
  • CliMedBERT: A Pre-trained Language Model for Climate and Health-related Text
  • Improving accuracy and convergence of federated learning edge computing methods for generalized DER forecasting applications in power grid
  • **Tutorials Track**:

    1. Disaster Risk Monitoring Using Satellite Imagery
    2. Machine Learning for Predicting Climate Extremes
    3. FourCastNet: A practical introduction to a state-of-the-art deep learning global weather emulator
    4. Automating the creation of LULC datasets

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