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
- Levee protected area detection for improved flood risk assessment in global hydrology models
- Bridging the Microwave Data Gap; Using Bayesian Deep Learning to “See” the Unseen
- Data-Driven Optimal Solver for Coordinating a Sustainable and Stable Power Grid
- Exploring Randomly Wired Neural Networks for Climate Model Emulation
- Closing the Domain Gap -- Blended Synthetic Imagery for Climate Object Detection
- Reconstruction of Grid Measurements in the Presence of Adversarial Attacks
- Bayesian State-Space SCM for Deforestation Baseline Estimation for Forest Carbon Credit
- Learn to Bid: Deep Reinforcement Learning with Transformer for Energy Storage Bidding in Energy and Contingency Reserve Markets
- Nowformer : A Locally Enhanced Temporal Learner for Precipitation Nowcasting
- Multimodal Wildland Fire Smoke Detection
- Dynamic weights enabled Physics-Informed Neural Network for simulating the mobility of Engineered Nano Particles in a contaminated aquifer
- Synthesis of Realistic Load Data: Adversarial Networks for Learning and Generating Residential Load Patterns
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
- Towards Low Cost Automated Monitoring of Life Below Water to De-risk Ocean-Based Carbon Dioxide Removal and Clean Power
- Estimating Heating Loads in Alaska using Remote Sensing and Machine Learning Methods
Chat is not available.