Initial Structure to Relaxed Energy (IS2RE)
4 papers with code • 1 benchmarks • 1 datasets
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From this observation we derive "Noisy Nodes", a simple technique in which we corrupt the input graph with noise, and add a noise correcting node-level loss.
We introduce a novel approach to modeling angular information between sets of neighboring atoms in a graph neural network.
Recent progress in Graph Neural Networks (GNNs) for modeling atomic simulations has the potential to revolutionize catalyst discovery, which is a key step in making progress towards the energy breakthroughs needed to combat climate change.
This work investigates this question by first developing the GemNet-OC model based on the large Open Catalyst 2020 (OC20) dataset.