Publications & Preprints

• Onur Teymur, Jackson Gorham, Marina Riabiz and Chris. J. Oates. “Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy.” AISTATS. April 2021. [arxiv]
• Jackson Gorham, Anant Raj and Lester Mackey. “Stochastic Stein Discrepancies.” Advances in Neural Information Processing Systems. December 2020. [arxiv] [code]
• Wilson Ye Chen, Alessandro Barp, François-Xavier Briol, Jackson Gorham, Mark Girolami, Lester Mackey and Chris. J. Oates. “Stein Point Markov Chain Monte Carlo.” International Conference on Machine Learning (ICML), June 2019. [arxiv]
• Jackson Gorham, Andrew Duncan, Sebastian Vollmer and Lester Mackey. “Measuring Sample Quality with Diffusions.” Annals of Applied Probability 2019, Vol. 29, No. 5, 2884-2928 [arxiv] [code]
• Wilson Ye Chen, Lester Mackey, Jackson Gorham, François-Xavier Briol and Chris J. Oates. “Stein Points.” International Conference on Machine Learning (ICML), July 2018. [arxiv]
• Jackson Gorham and Lester Mackey. “Measuring Sample Quality with Kernels.” International Conference on Machine Learning (ICML), August 2017. [arxiv] [code]
• Lester Mackey and Jackson Gorham. “Multivariate Stein Factors for a Class of Strongly Log-concave Distributions.” Electronic Communications in Probability 2016, Vol. 21, paper no. 56, 1-14. [arxiv]
• Jackson Gorham and Lester Mackey. “Measuring Sample Quality with Stein’s Method.” Advances in Neural Information Processing Systems. 2015. [arxiv] [code]
• Gunnar Carlsson, Jackson Gorham, Matthew Kahle and Jeremy Mason. “Computational Topology for Configuration Spaces of Hard Disks.” Physical Review E 85.1 (2012): 011303. [arxiv]
• Jackson Gorham. “A Computational Topology Approach to Hard Spheres in a Box.” Undergraduate Thesis, 2010. [pdf]