Initial Structure to Relaxed Energy (IS2RE)

4 papers with code • 1 benchmarks • 1 datasets

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Use these libraries to find Initial Structure to Relaxed Energy (IS2RE) models and implementations


Most implemented papers

Simple GNN Regularisation for 3D Molecular Property Prediction & Beyond

Namkyeong/NoisyNodes_Pytorch 15 Jun 2021

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

Open-Catalyst-Project/ocp 17 Jun 2021

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 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.

GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets

Open-Catalyst-Project/ocp 6 Apr 2022

This work investigates this question by first developing the GemNet-OC model based on the large Open Catalyst 2020 (OC20) dataset.