| Reinforcement Learning for Market Making in a Multi-agent Dealer Market S Ganesh, N Vadori, M Xu, H Zheng, P Reddy, M Veloso NeurIPS 2019 Workshop on Robust AI in Financial Services, 2019 | 79 | 2019 |
| A semi-Markovian modeling of limit order markets A Swishchuk, N Vadori SIAM Journal on Financial Mathematics 8 (1), 240-273, 2017 | 29 | 2017 |
| Smiling for the delayed volatility swaps A Swishchuk, N Vadori Wilmott, 62-73, 2014 | 21 | 2014 |
| Strong law of large numbers and central limit theorems for functionals of inhomogeneous Semi-Markov processes N Vadori, A Swishchuk Stochastic Analysis and Applications 33 (2), 213-243, 2015 | 20 | 2015 |
| Towards a fully RL-based Market Simulator L Ardon, N Vadori, T Spooner, M Xu, J Vann, S Ganesh ICAIF 2021, the 2nd ACM International Conference on AI in Finance, 2021 | 16 | 2021 |
| Calibration of Shared Equilibria in General Sum Partially Observable Markov Games N Vadori, S Ganesh, P Reddy, M Veloso NeurIPS 2020, 2020 | 14 | 2020 |
| Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty N Vadori, S Ganesh, P Reddy, M Veloso ICAIF 2020, the 1st ACM International Conference on AI in Finance, 2020 | 10 | 2020 |
| Factored Policy Gradients: Leveraging Structure for Efficient Learning in MOMDPs T Spooner, N Vadori, S Ganesh NeurIPS 2021, 2021 | 9 | 2021 |
| Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations N Vadori, L Ardon, S Ganesh, T Spooner, S Amrouni, J Vann, M Xu, ... Mathematical Finance, Special Issue on Machine Learning in Finance, 2022 | 4 | 2022 |
| Inhomogeneous random evolutions: limit theorems and financial applications N Vadori, A Swishchuk Mathematics 7 (5), 447, 2019 | 4 | 2019 |
| Calibration of Derivative Pricing Models: a Multi-Agent Reinforcement Learning Perspective N Vadori ICAIF 2023, the 4th ACM International Conference on AI in Finance, 2022 | 3 | 2022 |
| Consensus multiplicative weights update: Learning to learn using projector-based game signatures N Vadori, R Savani, T Spooner, S Ganesh ICML 2022, 2021 | 3 | 2021 |
| Semi-Markov Driven Models: Limit Theorems and Financial Applications NN Vadori PhD Thesis, 2015 | 3 | 2015 |
| Ordinal Potential-based Player Rating N Vadori, R Savani AISTATS 2024, 2023 | 2 | 2023 |
| Learning to Optimize Differentiable Games X Chen, N Vadori, T Chen, Z Wang ICML 2023, 2023 | 2 | 2023 |
| Convergence of random bounded linear operators in the Skorokhod space N Vadori, A Swishchuk Random Operators and Stochastic Equations 27 (2), 131-142, 2019 | 2 | 2019 |
| Method and system for simulation and calibration of markets N Vadori, S Ganesh, XU Mengda, PP Reddy, MM Veloso US Patent App. 17/451,720, 2022 | | 2022 |
| Systems and methods for risk-sensitive reinforcement learning N Vadori, S Ganesh, MM Veloso US Patent App. 17/154,825, 2021 | | 2021 |
Anatoliy SwishchukUniversity of CalgaryVerified email at ucalgary.ca
