CIFAR-10

CIFAR-10 is a dataset containing 60,000 32x32 color images in 10 different classes, commonly used to evaluate the performance of machine learning algorithms in image classification tasks.

Papers using CIFAR-10 (17)

Improving GANs by leveraging the quantum noise from real hardware2025 · 1 citesTypical Machine Learning Datasets as Low-Depth Quantum Circuits2025 · 1 citesFast and memory-efficient classical simulation of quantum machine learning via forward and backward gate fusion2026Fidelity-Preserving Quantum Encoding for Quantum Neural Networks2025Adversarially Robust Quantum Transfer Learning2025Multi-channel convolutional neural quantum embedding2025You Only Measure Once: On Designing Single-Shot Quantum Machine Learning Models2025Quantum Reservoir GAN2025A Qubit-Efficient Hybrid Quantum Encoding Mechanism for Quantum Machine Learning2025Addressing the Current Challenges of Quantum Machine Learning through Multi-Chip Ensembles2025Quantum Denoising Diffusion Models2024 · 2 citesFederated Quantum-Train with Batched Parameter Generation2024 · 2 citesQAHAN: A Quantum Annealing Hard Attention Network2024 · 2 citesLet the Quantum Creep In: Designing Quantum Neural Network Models by Gradually Swapping Out Classical Components2024 · 1 citesCTRQNets & LQNets: Continuous Time Recurrent and Liquid Quantum Neural Networks2024Enhancing Quantum Diffusion Models with Pairwise Bell State Entanglement2024Quantum Pointwise Convolution: A Flexible and Scalable Approach for Neural Network Enhancement2024