Generative AI to quantify uncertainty in weather forecasting
AutoBNN: Probabilistic time series forecasting with compositional bayesian neural networks
Computer-aided diagnosis for lung cancer screening
Using AI to expand global access to reliable flood forecasts
ScreenAI: A visual language model for UI and visually-situated language understanding
SCIN: A new resource for representative dermatology images
MELON: Reconstructing 3D objects from images with unknown poses
HEAL: A framework for health equity assessment of machine learning performance
Cappy: Outperforming and boosting large multi-task language models with a small scorer
Talk like a graph: Encoding graphs for large language models
Chain-of-table: Evolving tables in the reasoning chain for table understanding
Health-specific embedding tools for dermatology and pathology
Social learning: Collaborative learning with large language models
Croissant: a metadata format for ML-ready datasets
Google at APS 2024
VideoPrism: A foundational visual encoder for video understanding
Advances in private training for production on-device language models
Learning the importance of training data under concept drift
DP-Auditorium: A flexible library for auditing differential privacy
Graph neural networks in TensorFlow
A decoder-only foundation model for time-series forecasting
Intervening on early readouts for mitigating spurious features and simplicity bias
MobileDiffusion: Rapid text-to-image generation on-device
Mixed-input matrix multiplication performance optimizations
Exphormer: Scaling transformers for graph-structured data
Introducing ASPIRE for selective prediction in LLMs
AMIE: A research AI system for diagnostic medical reasoning and conversations
Can large language models identify and correct their mistakes?
Responsible AI at Google Research: User Experience Team
