99 citations · 275 across the 12 of their papers we have counts for
5 papers · 1 filter
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks
Louis Schatzki, Martin Larocca, Quynh T. Nguyen +2
Despite the great promise of quantum machine learning models, there are several challenges one must overcome before unlocking their full potential. For instance, models based on qu…
Theory for Equivariant Quantum Neural Networks
Quynh T. Nguyen, Louis Schatzki, Paolo Braccia +5
Quantum neural network architectures that have little-to-no inductive biases are known to face trainability and generalization issues. Inspired by a similar problem, recent breakth…
Representation Theory for Geometric Quantum Machine Learning
Michael Ragone, Paolo Braccia, Quynh T. Nguyen +5
Recent advances in classical machine learning have shown that creating models with inductive biases encoding the symmetries of a problem can greatly improve performance. Importatio…
A Hierarchy of Multipartite Correlations Based on Concentratable Entanglement
Louis Schatzki, Guangkuo Liu, M. Cerezo +1
Multipartite entanglement is one of the hallmarks of quantum mechanics and is central to quantum information processing. In this work we show that Concentratable Entanglement (CE),…
Tensor Rank and Other Multipartite Entanglement Measures of Graph States
Louis Schatzki, Linjian Ma, Edgar Solomonik +1
Graph states play an important role in quantum information theory through their connection to measurement-based computing and error correction. Prior work has revealed elegant conn…