Eric R. Anschuetz

21 papers A* 2Misc 2Journal 16Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Arbitrary Polynomial Separations in Trainable Quantum Machine Learning.
Quantum
Eric R. Anschuetz, Xun Gao
2026 J jnl
Optimizing Sparse SYK.
Quantum
Matthew Ding, Robbie King, Bobak T. Kiani, Eric R. Anschuetz
2025 A* conf
A Unified Theory of Quantum Neural Network Loss Landscapes.
ICLR
Eric R. Anschuetz
2025 J jnl
Decoded Quantum Interferometry Requires Structure.
CoRR
Eric R. Anschuetz, David Gamarnik, Jonathan Z. Lu
2025 J jnl
Fragmentation is Efficiently Learnable by Quantum Neural Networks.
CoRR
Mikhail Mints, Eric R. Anschuetz
2025 J jnl
Optimizing Sparse SYK.
CoRR
Matthew Ding, Robbie King, Bobak T. Kiani, Eric R. Anschuetz
2024 J jnl
A Unified Theory of Quantum Neural Network Loss Landscapes.
CoRR
Eric R. Anschuetz
2024 J jnl
Arbitrary Polynomial Separations in Trainable Quantum Machine Learning.
CoRR
Eric R. Anschuetz, Xun Gao
2024 J jnl
Combinatorial NLTS From the Overlap Gap Property.
Quantum
Eric R. Anschuetz, David Gamarnik, Bobak T. Kiani
2024 J jnl
Q-CHOP: Quantum constrained Hamiltonian optimization.
CoRR
Michael A. Perlin, Ruslan Shaydulin, Benjamin P. Hall, Pierre Minssen, Changhao Li, Kabir Dubey, Richard Rines, Eric R. Anschuetz, Marco Pistoia, Pranav Gokhale
2024 Misc conf
Quantifying the Limits of Classical Machine Learning Models Using Contextuality.
QCE
Eric R. Anschuetz, Mariesa Teo, Willers Yang, James Sud, Christopher Kang, Teague Tomesh, Frederic T. Chong
2023 J jnl
Does provable absence of barren plateaus imply classical simulability? Or, why we need to rethink variational quantum computing.
CoRR
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
2023 J jnl
Efficient classical algorithms for simulating symmetric quantum systems.
Quantum
Eric R. Anschuetz, Andreas Bauer, Bobak Toussi Kiani, Seth Lloyd
2023 J jnl
Training Quantum Boltzmann Machines with Coresets.
CoRR
Joshua Viszlai, Teague Tomesh, Pranav Gokhale, Eric R. Anschuetz, Frederic T. Chong
2022 A* conf
Critical Points in Quantum Generative Models.
ICLR
Eric R. Anschuetz
2022 Misc conf
Training Quantum Boltzmann Machines with Coresets.
QCE
Joshua Viszlai, Teague Tomesh, Pranav Gokhale, Eric R. Anschuetz, Frederic T. Chong
2021 J jnl
Enhancing Generative Models via Quantum Correlations.
CoRR
Xun Gao, Eric R. Anschuetz, Sheng-Tao Wang, J. Ignacio Cirac, Mikhail D. Lukin
2021 J jnl
Using Spectral Graph Theory to Map Qubits onto Connectivity-limited Devices.
ACM Trans. Quantum Comput.
Joseph X. Lin, Eric R. Anschuetz, Aram W. Harrow
2020 J jnl
Coreset Clustering on Small Quantum Computers.
CoRR
Teague Tomesh, Pranav Gokhale, Eric R. Anschuetz, Frederic T. Chong
2019 J jnl
Near-Term Quantum-Classical Associative Adversarial Networks.
CoRR
Eric R. Anschuetz, Cristian Zanoci
2017 — conf
Variational Quantum Factoring.
QTOP@NetSys
Eric R. Anschuetz, Jonathan Olson, Alán Aspuru-Guzik, Yudong Cao