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25 changes: 21 additions & 4 deletions README.md
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Expand Up @@ -56,7 +56,7 @@ PolyGraph discrepancy is a new metric we introduced, which provides the followin
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It also provides a number of other advantages over MMD which we discuss in our paper.
It also provides a number of other advantages over MMD which we discuss in [our paper](https://arxiv.org/abs/2510.06122).

## Installation

Expand Down Expand Up @@ -93,7 +93,7 @@ Here are a set of datasets and metrics this library provides:
- `SBMGraphDataset`
- `LobsterGraphDataset`

But they should not be used for benchmarking, due to unreliable metric estimates (see our paper for more details).
But they should not be used for benchmarking, due to unreliable metric estimates (see [our paper](https://arxiv.org/abs/2510.06122) for more details).

We provide larger datasets that should be used instead:
- `PlanarLGraphDataset`
Expand Down Expand Up @@ -176,7 +176,7 @@ for metric in tqdm(metrics):
```
## Example Benchmark

The following results mirror the tables from our paper. Bold indicates best, and underlined indicates second-best. Values are multiplied by 100 for legibility. Standard deviations are obtained with subsampling using `StandardPGDInterval` and `MoleculePGDInterval`. Specific parameters are discussed in the paper.
The following results mirror the tables from [our paper](https://arxiv.org/abs/2510.06122). Bold indicates best, and underlined indicates second-best. Values are multiplied by 100 for legibility. Standard deviations are obtained with subsampling using `StandardPGDInterval` and `MoleculePGDInterval`. Specific parameters are discussed in [the paper](https://arxiv.org/abs/2510.06122).

<div align="center">
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Expand Down Expand Up @@ -241,4 +241,21 @@ The following results mirror the tables from our paper. Bold indicates best, and
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</div>

<sub>* AutoGraph* denotes a variant that leverages additional training heuristics as described in the paper.</sub>
<sub>* AutoGraph* denotes a variant that leverages additional training heuristics as described in the [paper](https://arxiv.org/abs/2510.06122).</sub>


## Citing

To cite our paper:

```latex
@misc{krimmel2025polygraph,
title={PolyGraph Discrepancy: a classifier-based metric for graph generation},
author={Markus Krimmel and Philip Hartout and Karsten Borgwardt and Dexiong Chen},
year={2025},
eprint={2510.06122},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2510.06122},
}
```