Aarthi Sundaram

Childs, A. M., Kothari, R. ., Kovacs-Deak, M. ., Sundaram, A. ., & Wang, D. . (2022). Quantum divide and conquer. ArXiv. Retrieved from https://arxiv.org/abs/2210.06419 (Original work published October 2022)

Wang, D. ., Sundaram, A. ., Kothari, R. ., Kapoor, A. ., & Roetteler, M. . (2021). Quantum Algorithms for Reinforcement Learning with a Generative Model. Proceedings of the 38th International Conference on Machine Learning, PMLR, 139. Retrieved from https://proceedings.mlr.press/v139/wang21w.html (Original work published December 2021)

Arunachalam, S. ., Grilo, A. ., & Sundaram, A. . (2019). Quantum hardness of learning shallow classical circuits. ArXiv. Retrieved from https://arxiv.org/abs/1903.02840 (Original work published March 2019)

Gharibian, S. ., Santha, M. ., Sikora, J. ., Sundaram, A. ., & Yirka, J. . (2018). Quantum Generalizations of the Polynomial Hierarchy with Applications to QMA(2). In 43rd International Symposium on Mathematical Foundations of Computer Science (MFCS 2018). Schloss Dagstuhl – Leibniz-Zentrum für Informatik. http://doi.org/10.4230/LIPICS.MFCS.2018.58 (Original work published August 2018)

Sundaram, A. ., & Lackey, B. . (2018). Mathematical methods for resource-based type theories. ArXiv. Retrieved from https://arxiv.org/abs/1812.08726 (Original work published December 2018)