---
license: mit
---

# MNIST dataset used during the Perceval Quest challenge

This repository hosts a partial MNIST dataset used during the Perceval Quest as part of the
Hybrid AI Quantum Challenge. The dataset is stored under `data/` and split into
`train.csv` and `val.csv`.

This dataset is a subset of the original MNIST dataset that can be found [here](https://web.archive.org/web/20200430193701/http://yann.lecun.com/exdb/mnist/) and introduced in [LeCun et al., 1998a].

The Perceval Quest challenge lasted from November 2024 to March 2025. More than 64 teams participated in its first phase and 12 teams were selected amongst the finalist.

## Dataset structure

- `data/train.csv`
- `data/val.csv`

Each CSV contains two columns:

- `image`: a stringified list of 784 floats (28x28 grayscale image)
- `label`: the digit class (0-9)

## Load the dataset from `data/`

### Option 1: pandas

```python
import pandas as pd

train_df = pd.read_csv("./data/train.csv")
val_df = pd.read_csv("./data/val.csv")
```

### Option 2: PyTorch Dataset (provided)

```python
from data_utils import MNIST_partial

train_set = MNIST_partial(data="./data", split="train")
val_set = MNIST_partial(data="./data", split="val")
```

## References
- Dataset: [LeCun et al., 1998a] Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. "Gradient-based learning applied to document recognition." Proceedings of the IEEE, 86(11):2278-2324, November 1998.
- Paper: NOTTON, Cassandre, APOSTOLOU, Vassilis, SENELLART, Agathe, et al.
  Establishing Baselines for Photonic Quantum Machine Learning: Insights from an Open,
  Collaborative Initiative. arXiv preprint arXiv:2510.25839, 2025.
- Repository: https://github.com/Quandela/HybridAIQuantum-Challenge/tree/main