Ryan Babbush

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 9

Top Topics

Bayesian Network Structure Learning

Stochastic Gradient

Top Venues

Publications

Alexander Schmidhuber, Ryan O'Donnell, Robin Kothari, Ryan Babbush
Quartic quantum speedups for planted inference. CoRR (2024)
Ryan Babbush, Dominic W. Berry, Robin Kothari, Rolando D. Somma, Nathan Wiebe
. FOCS (2023)
Hsin-Yuan Huang, Michael Broughton, Jordan Cotler, Sitan Chen, Jerry Li, Masoud Mohseni, Hartmut Neven, Ryan Babbush, Richard Kueng, John Preskill, Jarrod R. McClean
Quantum advantage in learning from experiments. CoRR (2021)
Nicholas C. Rubin, Klaas Gunst, Alec White, Leon Freitag, Kyle Throssell, Garnet Kin-Lic Chan, Ryan Babbush, Toru Shiozaki
The Fermionic Quantum Emulator. Quantum 5 (2021)
Marco Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, Patrick J. Coles
Variational Quantum Algorithms. CoRR (2020)
Ian D. Kivlichan, Craig Gidney, Dominic W. Berry, Nathan Wiebe, Jarrod R. McClean, Wei Sun, Zhang Jiang, Nicholas Rubin, Austin G. Fowler, Alán Aspuru-Guzik, Hartmut Neven, Ryan Babbush
Improved Fault-Tolerant Quantum Simulation of Condensed-Phase Correlated Electrons via Trotterization. Quantum 4 (2020)
Hsin-Yuan Huang, Michael Broughton, Masoud Mohseni, Ryan Babbush, Sergio Boixo, Hartmut Neven, Jarrod R. McClean
Power of data in quantum machine learning. CoRR (2020)
Guillaume Verdon, Michael Broughton, Jarrod R. McClean, Kevin J. Sung, Ryan Babbush, Zhang Jiang, Hartmut Neven, Masoud Mohseni
Learning to learn with quantum neural networks via classical neural networks. CoRR (2019)
Jarrod R. McClean, Sergio Boixo, Vadim N. Smelyanskiy, Ryan Babbush, Hartmut Neven
Barren plateaus in quantum neural network training landscapes. CoRR (2018)
Ryan Babbush, Vasil S. Denchev, Nan Ding, Sergei Isakov, Hartmut Neven
Construction of non-convex polynomial loss functions for training a binary classifier with quantum annealing. CoRR (2014)
Nan Ding, Youhan Fang, Ryan Babbush, Changyou Chen, Robert D. Skeel, Hartmut Neven
Bayesian Sampling Using Stochastic Gradient Thermostats. NIPS (2014)
Bryan O'Gorman, Alejandro Perdomo-Ortiz, Ryan Babbush, Alán Aspuru-Guzik, Vadim Smelyanskiy
Bayesian Network Structure Learning Using Quantum Annealing. CoRR (2014)