├── figs
└── HOG-Diff-framework.png
└── readme.md
/figs/HOG-Diff-framework.png:
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https://raw.githubusercontent.com/Yiminghh/HOG-Diff/c44dbc9cb079e7d8f140528458971bd5e4db6eb8/figs/HOG-Diff-framework.png
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/readme.md:
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1 |
HOG-Diff: Higher-Order Guided Diffusion for Graph Generation
2 |
3 |
4 |
5 |
6 | Official Implementations of HOG-Diff.
7 | In this work, we propose a novel Higher-order Guided
8 | Diffusion (HOG-Diff) model that follows a coarse-to-fine generation curriculum and is guided by higher-order information, enabling the progressive generation of authentic graphs with inherent topological structures.
9 |
10 | 🚀 **We are continuously updating this repository and will release the complete code after the paper is accepted.**
11 |
12 |
13 |
14 |

15 |
16 |
17 | ---
18 |
19 |
20 |
21 |
22 | ## Environment Setup
23 | This code was tested with PyTorch 2.0.0, cuda 11.8 and torch_geometrics 2.6.1
24 |
25 | 1️⃣ Download anaconda/miniconda if needed
26 |
27 | 2️⃣ Create and Activate a Python Virtual Environment
28 | ```
29 | conda create -n HoGD_py39 python=3.9
30 | conda activate HoGD_py39
31 | ```
32 | 3️⃣ Install Dependencies
33 |
34 | Use the provided requirements.txt file to install all dependencies:
35 | ```
36 | pip install -r requirements.txt
37 | ```
38 |
39 | 4️⃣ Compile the ORCA Program (for Graph Generation Evaluation)
40 |
41 | For evaluating generic graph generation tasks, compile the [ORCA](http://www.biolab.si/supp/orca/orca.html) program by running the following command:
42 |
43 | ```sh
44 | cd evaluation/orca
45 | g++ -O2 -std=c++11 -o orca orca.cpp
46 | ```
47 |
48 |
49 |
50 | # Running Experiments
51 |
52 | To train and sample graphs using HOG-Diff, use the following commands:
53 |
54 |
55 | ```shell
56 | CUDA_VISIBLE_DEVICES=0 python main.py --config config_name --mode train_ho
57 | CUDA_VISIBLE_DEVICES=0 python main.py --config config_name --mode train_OU
58 | CUDA_VISIBLE_DEVICES=0 python main.py --config config_name --mode sample
59 | ```
60 |
61 | Replace config_name with the appropriate configuration file.
62 |
63 | # Citation
64 | Please cite our work if you find our code/paper is useful to your work. :
65 | ```latex
66 |
67 | ```
68 |
69 |
70 |
71 | 🍀 **Thank you for your interest in our work.** 🍀
72 |
73 | If you have any questions or encounter any issues while using our code, please don't hesitate to raise an issue or reach out to us directly.
74 |
75 |
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