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Found 5 papers, 2 papers with code
Learning shallow quantum circuits
Despite fundamental interests in learning quantum circuits, the existence of a computationally efficient algorithm for learning shallow quantum circuits remains an open question.
A Topological Perspective on Demystifying GNN-Based Link Prediction Performance
Despite the widespread belief that low-degree nodes exhibit poorer LP performance, our empirical findings provide nuances to this viewpoint and prompt us to propose a better metric, Topological Concentration (TC), based on the intersection of the local subgraph of each node with the ones of its neighbors.
Fairness and Diversity in Recommender Systems: A Survey
Additionally, motivated by the concepts of user-level and item-level fairness, we broaden the understanding of diversity to encompass not only the item level but also the user level.
A rigorous and robust quantum speed-up in supervised machine learning
Over the past few years several quantum machine learning algorithms were proposed that promise quantum speed-ups over their classical counterparts.
Learning to Describe Scenes with Programs
We are able to understand the higher-level, abstract regularities within the scene such as symmetry and repetition.
