Dissipation as a resource for quantum reservoir computing

Noise induced shallow circuits and absence of barren plateaus

Generative Quantum Machine Learning via Denoising Diffusion Probabilistic Models

On fundamental aspects of quantum extreme learning machines

Does provable absence of barren plateaus imply classical simulability？

Mapping out phase diagrams with generative classifiers

Random Natural Gradient

The discrete adiabatic quantum linear system solver has lower constant factors than the ra

From explainable NLP to quantum dynamics prediction

On the expressivity of embedding quantum kernels

Symmetry invariant quantum machine learning force fields

Provable Advantage of Parameterized Quantum Circuit in Function Approximation

Model Independent Learning of Quantum Phases of Matter with Quantum Convolutional Neural Networks

Evaluating analytic gradients of pulse programs on quantum computers

Quantum Regularized Least Squares

QRAM A Survey and Critique

Post-variational quantum neural networks

Phase transition in Random Circuit Sampling

Understanding quantum machine learning also requires rethinking generalization

Systems Architecture for Quantum Random Access Memory

Transition role of entangled data in quantum machine learning

Classical Verification of Quantum Learning

Trainability barriers and opportunities in quantum generative modeling

On quantum backpropagation, information reuse, and cheating measurement collapse

Comparing Generalization of Quantum and Classical Generative Models towards Practical QA

Towards Provably Efficient Quantum Algorithms for Large scale Machine learning Models

On the Role of Entanglement and Statistics in Learnining

Exponentially Improved Efficient Machine Leaning for Quantum Many body States

Learning quantum systems via out of time order correlators

Learning to predict arbitrary quantum processes