Eric R. Anschuetz

According to our database, Eric R. Anschuetz authored at least 18 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Optimizing Sparse SYK.

Matthew Ding, Robbie King, Bobak T. Kiani, Eric R. Anschuetz

Quantum, 2026

Arbitrary Polynomial Separations in Trainable Quantum Machine Learning.

Eric R. Anschuetz, Xun Gao

Quantum, 2026

2025

Fragmentation is Efficiently Learnable by Quantum Neural Networks.

Mikhail Mints, Eric R. Anschuetz

CoRR, December, 2025

Decoded Quantum Interferometry Requires Structure.

Eric R. Anschuetz, David Gamarnik, Jonathan Z. Lu

CoRR, September, 2025

k-Contextuality as a Heuristic for Memory Separations in Learning.

Mariesa Teo, Willers Yang, James Sud, Teague Tomesh, Frederic T. Chong, Eric R. Anschuetz

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2025

A Unified Theory of Quantum Neural Network Loss Landscapes.

Eric R. Anschuetz

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Combinatorial NLTS From the Overlap Gap Property.

Eric R. Anschuetz, David Gamarnik, Bobak T. Kiani

Quantum, 2024

Q-CHOP: Quantum constrained Hamiltonian optimization.

Michael A. Perlin, Ruslan Shaydulin, Benjamin P. Hall, Pierre Minssen, Changhao Li, Kabir Dubey, Richard Rines, Eric R. Anschuetz, Marco Pistoia, Pranav Gokhale

CoRR, 2024

Quantifying the Limits of Classical Machine Learning Models Using Contextuality.

Eric R. Anschuetz, Mariesa Teo, Willers Yang, James Sud, Christopher Kang, Teague Tomesh, Frederic T. Chong

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2024

2023

Efficient classical algorithms for simulating symmetric quantum systems.

Eric R. Anschuetz, Andreas Bauer, Bobak Toussi Kiani, Seth Lloyd

Quantum, November, 2023

Does provable absence of barren plateaus imply classical simulability? Or, why we need to rethink variational quantum computing.

Marco Cerezo, Martin Larocca, Diego García-Martín, Nelson L. Diaz, Paolo Braccia, Enrico Fontana, Manuel S. Rudolph, Pablo Bermejo, Aroosa Ijaz, Supanut Thanasilp, Eric R. Anschuetz, Zoë Holmes

CoRR, 2023

2022

Training Quantum Boltzmann Machines with Coresets.

Joshua Viszlai, Teague Tomesh, Pranav Gokhale, Eric R. Anschuetz, Frederic T. Chong

Proceedings of the IEEE International Conference on Quantum Computing and Engineering, 2022

Critical Points in Quantum Generative Models.

Eric R. Anschuetz

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Using Spectral Graph Theory to Map Qubits onto Connectivity-limited Devices.

Joseph X. Lin, Eric R. Anschuetz, Aram W. Harrow

ACM Trans. Quantum Comput., March, 2021

Enhancing Generative Models via Quantum Correlations.

Xun Gao, Eric R. Anschuetz, Sheng-Tao Wang, J. Ignacio Cirac, Mikhail D. Lukin

CoRR, 2021

2020

Coreset Clustering on Small Quantum Computers.

Teague Tomesh, Pranav Gokhale, Eric R. Anschuetz, Frederic T. Chong

CoRR, 2020

2019

Near-Term Quantum-Classical Associative Adversarial Networks.

Eric R. Anschuetz, Cristian Zanoci

CoRR, 2019

2017

Variational Quantum Factoring.

Eric R. Anschuetz, Jonathan Olson, Alán Aspuru-Guzik, Yudong Cao

Proceedings of the Quantum Technology and Optimization Problems, 2017