Initial Structure to Relaxed Energy (IS2RE)
3 papers with code • 1 benchmarks • 1 datasets
Most implemented papers
Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond
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
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.