| txie-93/cgcnn |
262 |
|
0 |
0 |
over 4 years ago |
0 |
|
9 |
mit |
Python |
| Crystal graph convolutional neural networks for predicting material properties. |
| ContextLab/storytelling-with-data |
97 |
|
0 |
0 |
about 2 years ago |
0 |
|
1 |
mit |
Jupyter Notebook |
| Course materials for Dartmouth Course: Storytelling with Data (PSYC 81.09). |
| awslabs/amazon-asdi |
75 |
|
0 |
0 |
over 2 years ago |
0 |
|
2 |
apache-2.0 |
Jupyter Notebook |
| Docs and supporting material for the Amazon Sustainability Data Initiative. |
| MLMI2-CSSI/foundry |
71 |
|
0 |
2 |
about 2 years ago |
29 |
November 13, 2023 |
92 |
mit |
Python |
| Simplifying the discovery and usage of machine-learning ready datasets in materials science and chemistry |
| CederGroupHub/text-mined-synthesis_public |
52 |
|
0 |
0 |
over 2 years ago |
0 |
|
2 |
|
Python |
| Codes for text-mined solid-state reactions dataset |
| superlouis/GATGNN |
51 |
|
0 |
0 |
over 3 years ago |
0 |
|
2 |
mit |
Python |
| Pytorch Repository for our work: Graph convolutional neural networks with global attention for improved materials property prediction |
| GLambard/SMILES-X |
38 |
|
0 |
0 |
about 3 years ago |
0 |
|
1 |
mit |
Jupyter Notebook |
| Autonomous characterization of molecular compounds from small datasets without descriptors |
| nuitrcs/pythonworkshops |
29 |
|
0 |
0 |
almost 3 years ago |
0 |
|
0 |
|
CSS |
| Materials for Python workshops |
| yannick-lc/iccv2019-triplet-loss |
23 |
|
0 |
0 |
about 6 years ago |
0 |
|
0 |
agpl-3.0 |
Jupyter Notebook |
| Implementation of method described in http://openaccess.thecvf.com/content_ICCV_2019/papers/Le_Cacheux_Modeling_Inter_and_Intra-Class_Relations_in_the_Triplet_Loss_for_ICCV_2019_paper.pdf |
| soumyasanyal/mt-cgcnn |
21 |
|
0 |
0 |
over 6 years ago |
0 |
|
0 |
other |
Python |
| NeurIPS 2018 MLMM Workshop: Integrating Crystal Graph Convolutional Neural Network with Multitask Learning for Material Property Prediction |
