README.md

metadata

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 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

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)

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