Graph Neural Networks (GNN)
AI Weather Prediction Gains Traction: U.S. working with Google Weather Lab AI to improve storm forecasts
The U.S. government is using AI to predict the paths of hurricanes.
Graph Neural Networks (GNN)
25 Posts
Graph Neural Networks (GNN)
Robot, Find My Keys: A machine learning model for robots to predict the location of objects in households
Researchers proposed a way for robots to find objects in households where things get moved around. Andrey Kurenkov and colleagues at Stanford University introduced Node Edge Predictor, a model that learned to predict where objects were located in houses.
Graph Neural Networks (GNN)
Robot, Find My Keys: A machine learning model for robots to predict the location of objects in households
Researchers proposed a way for robots to find objects in households where things get moved around. Andrey Kurenkov and colleagues at Stanford University introduced Node Edge Predictor, a model that learned to predict where objects were located in houses.
Graph Neural Networks (GNN)
Long-Range Weather Forecasts: This ML-based forecast simulator outperformed medium-range forecast systems.
Machine learning models have predicted weather a few days ahead of time. A new approach substantially extends the time horizon. Remi Lam and colleagues at Google developed GraphCast, a weather-forecasting system based on graph neural networks (GNNs).
Graph Neural Networks (GNN)
Long-Range Weather Forecasts: This ML-based forecast simulator outperformed medium-range forecast systems.
Machine learning models have predicted weather a few days ahead of time. A new approach substantially extends the time horizon. Remi Lam and colleagues at Google developed GraphCast, a weather-forecasting system based on graph neural networks (GNNs).
Graph Neural Networks (GNN)
What a Molecule’s Structure Reveals: Baidu Creates AI to Classify Molecular Properties
The authors trained a modified GNN on a dataset of 18 million molecules to find molecular properties.
Graph Neural Networks (GNN)
What a Molecule’s Structure Reveals: Baidu Creates AI to Classify Molecular Properties
The authors trained a modified GNN on a dataset of 18 million molecules to find molecular properties.
Graph Neural Networks (GNN)
A Transformer for Graphs: New Method for Processing Graph Data with Transformers
Transformers can learn a lot from sequential data like words in a book, but they’ve shown limited ability to learn from data in the form of a graph. A new transformer variant gives graphs due attention.
Graph Neural Networks (GNN)
A Transformer for Graphs: New Method for Processing Graph Data with Transformers
Transformers can learn a lot from sequential data like words in a book, but they’ve shown limited ability to learn from data in the form of a graph. A new transformer variant gives graphs due attention.
Graph Neural Networks (GNN)
Airfoils Automatically Optimized: DeepMind AI Research Simulates Fluid Dynamics
Engineers who design aircraft, aqueducts, and other objects that interact with air and water use numerical simulations to test potential shapes, but they rely on trial and error to improve their designs. A neural simulator can optimize the shape itself.
Graph Neural Networks (GNN)
Airfoils Automatically Optimized: DeepMind AI Research Simulates Fluid Dynamics
Engineers who design aircraft, aqueducts, and other objects that interact with air and water use numerical simulations to test potential shapes, but they rely on trial and error to improve their designs. A neural simulator can optimize the shape itself.
Graph Neural Networks (GNN)
Who Needs Training? Graph neural network selects optimal weights for image tasks.
When you’re training a neural network, it takes a lot of computation to optimize its weights using an iterative algorithm like stochastic gradient descent. Wouldn’t it be great to compute the best parameter values in one pass? A new method takes a substantial step in that direction.
Graph Neural Networks (GNN)
Who Needs Training? Graph neural network selects optimal weights for image tasks.
When you’re training a neural network, it takes a lot of computation to optimize its weights using an iterative algorithm like stochastic gradient descent. Wouldn’t it be great to compute the best parameter values in one pass? A new method takes a substantial step in that direction.
Graph Neural Networks (GNN)
Roadblocks to Regulation: Why laws to regulate AI usually fail.
Most U.S. state agencies use AI without limits or oversight. An investigative report probed reasons why efforts to rein them in have made little headway. Since 2018, nearly every proposed bill aimed at studying or controlling how state agencies use automated decision systems.
Graph Neural Networks (GNN)
Roadblocks to Regulation: Why laws to regulate AI usually fail.
Most U.S. state agencies use AI without limits or oversight. An investigative report probed reasons why efforts to rein them in have made little headway. Since 2018, nearly every proposed bill aimed at studying or controlling how state agencies use automated decision systems.
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