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