| Tensor-structured coupled cluster theory R Schutski, J Zhao, TM Henderson, GE Scuseria The Journal of chemical physics 147 (18), 2017 | 71 | 2017 |
| Tensor network quantum simulator with step-dependent parallelization D Lykov, R Schutski, A Galda, V Vinokur, Y Alexeev 2022 IEEE International Conference on Quantum Computing and Engineering (QCE …, 2022 | 55 | 2022 |
| Multireference symmetry-projected variational approaches for ground and excited states of the one-dimensional Hubbard model R Rodríguez-Guzmán, CA Jiménez-Hoyos, R Schutski, GE Scuseria Physical Review B 87 (23), 235129, 2013 | 54 | 2013 |
| Adaptive algorithm for quantum circuit simulation R Schutski, D Lykov, I Oseledets Physical Review A 101 (4), 042335, 2020 | 28 | 2020 |
| TTOpt: A maximum volume quantized tensor train-based optimization and its application to reinforcement learning K Sozykin, A Chertkov, R Schutski, AH Phan, AS Cichocki, I Oseledets Advances in Neural Information Processing Systems 35, 26052-26065, 2022 | 24 | 2022 |
| Tensor-decomposition techniques for ab initio nuclear structure calculations: From chiral nuclear potentials to ground-state energies A Tichai, R Schutski, GE Scuseria, T Duguet Physical Review C 99 (3), 034320, 2019 | 22 | 2019 |
| Comparing the accuracy of perturbative and variational calculations for predicting fundamental vibrational frequencies of dihalomethanes SV Krasnoshchekov, RS Schutski, NC Craig, M Sibaev, DL Crittenden The Journal of chemical physics 148 (8), 2018 | 21 | 2018 |
| Analytic energy gradient for the projected Hartree–Fock method R Schutski, CA Jiménez-Hoyos, GE Scuseria The Journal of Chemical Physics 140 (20), 2014 | 17 | 2014 |
| Simple heuristics for efficient parallel tensor contraction and quantum circuit simulation R Schutski, T Khakhulin, I Oseledets, D Kolmakov Physical Review A 102 (6), 062614, 2020 | 16 | 2020 |
| Quantum circuit simulation RS Schutski, IV Oseledets, YA Zotov, DS Kolmakov US Patent App. 17/717,914, 2022 | 2 | 2022 |
| Learning elimination ordering for tree decomposition problem T Khakhulin, R Schutski, I Oseledets Learning Meets Combinatorial Algorithms at NeurIPS2020, 2020 | 2 | 2020 |
| Graph Convolutional Policy for Solving Tree Decomposition via Reinforcement Learning Heuristics T Khakhulin, R Schutski, I Oseledets arXiv preprint arXiv:1910.08371, 2019 | | 2019 |
| Tensor Structured Coupled Cluster Methods R Schutski Rice University, 2018 | | 2018 |
Gustavo E. ScuseriaWelch Professor of Chemistry, Physics & Astronomy, and Materials Science & NanoEngineeringVerified email at rice.edu
