By identifying an instrumental variable correlated with the variableX butunrelated tothe confounders, researchers can isolate the exogenous variation inX and estimate acausal relationship betweenX andY.

In this paper, we propose a novel and powerful method to harness Bayesian optimization for V ariational Quantum Eigensolvers (VQEs)--a hybrid quantum-classical protocol used to approximate the ground state of a quantum Hamiltonian.

In this work, we ask two key questions. First, in a more realistic setting where only a CPU is available, is the GNN model still competitive?

Most of the existing acquisition policies are only one-step optimal, that is, optimal if the decision horizonwereone.