Classical Verification of Quantum Learning

Learning bounds and guarantees for testing (quantum) hypotheses

Exponential separations between classical and quantum learners

Classical simulations of noisy variational quantum circuits

Non-IID Quantum Federated Learning with One-shot Communication Complexity

Quantum models and data through a precomputation lens

Demystify Problem-Dependent Power of Quantum Neural Networks on Multi-Class Classification

Transition role of entangled data in quantum machine learning

The power and limitations of learning quantum dynamics incoherently

Understanding generalization with quantum geometry

Understanding quantum machine learning also requires rethinking generalization