Initial Structure to Relaxed Energy (IS2RE)
3 papers with code • 1 benchmarks • 1 datasets
OC20
Most implemented papers
Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond
Namkyeong/NoisyNodes_Pytorch
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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.
Rotation Invariant Graph Neural Networks using Spin Convolutions
We introduce a novel approach to modeling angular information between sets of neighboring atoms in a graph neural network.
Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations
intellabs/matsciml
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ICLR 2022
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.
