Shouvanik Chakrabarti

Pistoia, M. ., Ahmad, S. ., Ajagekar, A. ., Buts, A. ., Chakrabarti, S. ., Herman, D. ., … Yalovetzky, R. . (2021). Quantum Machine Learning for Finance. ArXiv. Retrieved from https://arxiv.org/abs/2109.04298 (Original work published September 2021)

Chakrabarti, S. ., Krishnakumar, R. ., Mazzola, G. ., Stamatopoulos, N. ., Woerner, S. ., & Zeng, W. . (2021). A Threshold for Quantum Advantage in Derivative Pricing. Quantum, 5, 463. http://doi.org/10.22331/q-2021-06-01-463 (Original work published June 2021)

Li, T. ., Wang, C. ., Chakrabarti, S. ., & Wu, X. . (2021). Sublinear Classical and Quantum Algorithms for General Matrix Games. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 8465–8473). Association for the Advancement of Artificial Intelligence (AAAI). http://doi.org/10.1609/aaai.v35i10.17028 (Original work published May 2021)

Zhu, S. ., Hung, S.-H. ., Chakrabarti, S. ., & Wu, X. . (2020). On the principles of differentiable quantum programming languages. In Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation (pp. 272–285). ACM. http://doi.org/10.1145/3385412.3386011 (Original work published June 2020)

Chakrabarti, S. ., Childs, A. M., Li, T. ., & Wu, X. . (2020). Quantum algorithms and lower bounds for convex optimization. Quantum, 4. http://doi.org/10.22331/q-2020-01-13-221 (Original work published January 2020)

Chakrabarti, S. ., Huang, Y. ., Li, T. ., Feizi, S. ., & Wu, X. . (2019). Quantum Wasserstein Generative Adversarial Networks. Advances in Neural Information Processing Systems (NIPS), 32. http://doi.org/https://papers.nips.cc/paper/8903-quantum-wasserstein-generative-adversarial-networks.pdf (Original work published October 2019)

Li, T. ., Chakrabarti, S. ., & Wu, X. . (2019). Sublinear quantum algorithms for training linear and kernel-based classifiers. Proceedings of the 36th International Conference on Machine Learning (ICML 2019) PMLR, 97, 3815–3824. Retrieved from https://arxiv.org/abs/1904.02276 (Original work published April 2019)