Updated 2021 04

Some Random Quantum Reviews (not included ongoing research on the theory part)

(1) Quantum Graph Neural Networks

  • Introduce GNN format to Quantum network. The paper wants to highlight the advantages of quantum chemistry, but it is still limited on the scale of qubits.

In short, I think the question is still to remark “why we really need a quantum circuit layer,” maybe for universal approximation with better representation. But it is not fully convincing to me. However, we do have some advantages from the system perspective.

It would be fun if this QGNN work actually incorporates some chemistry and drug discovery.

(2) Variational quantum policies for reinforcement learning

  • Introduce policy gradient estimation with VQC learning.

Although it is less supervised than VQC works for policy gradient, I am still very interested that it shows some computational results.

I also found that the recent VQC works are very likely got inspired by Yen-Chi VQC design, which is more empirical running on simulator or NISQ.

Both Yen-Chi and I are still enjoying this work when sufficient discussion are motivated.

(3) Quantum Self-Supervised Learning

  • introduce a contrastive loss in a self-supervised learning favor

VQC as encoder or kernel learning is intuitive. When the VQC learning requires very few parameters, the few-shot setup could be interesting.