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Found 4 papers, 3 papers with code
Derivative-free tree optimization for complex systems
Our method demonstrates wide applicability to a wide range of real-world complex systems spanning materials, physics, and biology, considerably outperforming state-of-the-art algorithms.
Traffic4cast at NeurIPS 2022 -- Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors
We only provide vehicle count data from spatially sparse stationary vehicle detectors in these three cities as model input for this task.
From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning
Here, an MD dataset containing 3, 218 different protein-ligand complexes is curated, and Dynaformer, a graph-based deep learning model is further developed to predict the binding affinities by learning the geometric characteristics of the protein-ligand interactions from the MD trajectories.
Machine-learning-enhanced time-of-flight mass spectrometry analysis
Mass spectrometry is a widespread approach to work out what are the constituents of a material.
