… exists between efficient quantum learnability and efficient clasical learnability. Undcr a widely
held … -time learnable in the quantum version but not in the classical version of the model. …

… learning algorithm must have a polynomial-time classical … quantum learnability and efficient
classical learnability. Under a widely held computational hardness assumption for classical …

… Here we study the comparative power of classical and quantum learners for … learnable
by a classical generative modelling algorithm, but for which we construct an efficient quantum …

… Intuitively, this result means that anything we can do with quantum advice, we can also do
with classical advice, provided we are willing to use exponentially more computation time to …

… Our work provides theoretical guidance for developing advanced QNNs and opens up
avenues for exploring quantum advantages beyond hybrid quantum-classical learning protocols …

… of the underlying probability distribution, and evaluate the corresponding learnability of
the associated samples. We perform such test with both quantum and classical samples. For …

… by common quantum data sources. In this paper, we build a hybrid quantum-classical
neural network with deep residual learning (Res-HQCNN) with graph-structured quantum data. …

… This theorem shows that every set of quantum states C is PAC learnable with respect to
measurements M (distributed according to D) with only a linear in n number of data points. To …

… 13] significantly extended the set of classical learnable quantum states to states which lies
in the same Lindbladian phase. With respect to their works, our findings establish a definitive …

… Moreover, we integrate the classical fully connected layer with PQCs to form a new … quantum
classical fully connected layer, which consists of two classical layers and one quantum layer…