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- [2003. 03123] Directional Message Passing for Molecular Graphs
We leverage these innovations to construct the directional message passing neural network (DimeNet) DimeNet outperforms previous GNNs on average by 76% on MD17 and by 31% on QM9 Our implementation is available online
- GitHub - gasteigerjo dimenet: DimeNet and DimeNet++ models, as proposed . . .
DimeNet and DimeNet++ models, as proposed in "Directional Message Passing for Molecular Graphs" (ICLR 2020) and "Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules" (NeurIPS-W 2020)
- DimeNet – 图神经网络公社
DimeNet（Directional Message Passing Neural Network）是一种专门用于分子图结构的神经网络，在预测分子性质和模拟分子间相互作用方面表现出色。 DimeNet 的独特之处在于它引入了方向性消息传递机制，使其能够更好地捕捉分子中的几何和角度信息。
- 图神经网络和分子表征：3. 不变网络最后的辉煌_dimenet-CSDN博客
本篇博客，我们将依次介绍首次纳入角度信息的DimeNet（2020 ICLR），受DimeNet启发的GemNet (NeurIPS 2021)，PAINN（2021 ICML）和SphereNet（2022 ICLR）以及做到局域完备性的ComENet（NeurIPS 2022）。
- 论文笔记35|directional message passing for molecular graphs
定向消息传递神经网络（DimeNet）：一种新颖的 GNN，利用这些创新为分子预测设定了新的技术水平，并且适用于预测分子特性和分子动力学模拟。
- 论文笔记 - 等变图神经网络 | Yufei Luos Blog
作者设计的 DimeNet 主要是为了做回归任务，即预测连续型的分子性质，如势能、偶极矩、毒性等。 网络的输入仅为原子序数 z = {z 1, …, z n} 和原子的位置 X = {x 1, …, x n}，输入为一个实数域上的标量，因此网络可以简单地表示为函数 f θ: {X, z} → R。
- torch_geometric. nn. models. DimeNet — pytorch_geometric documentation
The directional message passing neural network (DimeNet) from the “Directional Message Passing for Molecular Graphs” paper DimeNet transforms messages based on the angle between them in a rotation-equivariant fashion
- Dimenet - Data Analytics and Machine Learning - TUM
First, we propose the DimeNet++ model, which is 8x faster and 10% more accurate than the original DimeNet on the QM9 benchmark of equilibrium molecules Second, we validate DimeNet++ on highly reactive molecules by developing the challenging COLL dataset, which contains distorted configurations of small molecules during collisions
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