Bagnoli, Mark, and Ted Bergstrom. 1989. “Log-Concave Probability and Its Applications,” 17.
Brosse, Nicolas, Éric Moulines, and Alain Durmus. 2018. “The Promises and Pitfalls of Stochastic Gradient Langevin Dynamics.”
In Proceedings of the 32nd International Conference on Neural Information Processing Systems
, 8278–88. NIPS’18. Red Hook, NY, USA: Curran Associates Inc.
Castellani, Tommaso, and Andrea Cavagna. 2005. “Spin-Glass Theory for Pedestrians.” Journal of Statistical Mechanics: Theory and Experiment
2005 (05): P05012.
Duane, Simon, A. D. Kennedy, Brian J. Pendleton, and Duncan Roweth. 1987. “Hybrid Monte Carlo.” Physics Letters B
195 (2): 216–22.
Durmus, Alain, and Eric Moulines. 2016. “High-Dimensional Bayesian Inference via the Unadjusted Langevin Algorithm.” arXiv:1605.01559 [Math, Stat]
Garbuno-Inigo, Alfredo, Franca Hoffmann, Wuchen Li, and Andrew M. Stuart. 2020. “Interacting Langevin Diffusions: Gradient Structure and Ensemble Kalman Sampler.” SIAM Journal on Applied Dynamical Systems
19 (1): 412–41.
Girolami, Mark, and Ben Calderhead. 2011. “Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods.” Journal of the Royal Statistical Society: Series B (Statistical Methodology)
73 (2): 123–214.
Hodgkinson, Liam, Robert Salomone, and Fred Roosta. 2019. “Implicit Langevin Algorithms for Sampling From Log-Concave Densities.” arXiv:1903.12322 [Cs, Stat]
Mandt, Stephan, Matthew D. Hoffman, and David M. Blei. 2017. “Stochastic Gradient Descent as Approximate Bayesian Inference.” JMLR
Mangoubi, Oren, and Aaron Smith. 2017. “Rapid Mixing of Hamiltonian Monte Carlo on Strongly Log-Concave Distributions.” arXiv:1708.07114 [Math, Stat]
Saumard, Adrien, and Jon A. Wellner. 2014. “Log-Concavity and Strong Log-Concavity: A Review.” arXiv:1404.5886 [Math, Stat]
Welling, Max, and Yee Whye Teh. 2011. “Bayesian Learning via Stochastic Gradient Langevin Dynamics.”
In Proceedings of the 28th International Conference on International Conference on Machine Learning
, 681–88. ICML’11. Madison, WI, USA: Omnipress.
Xifara, T., C. Sherlock, S. Livingstone, S. Byrne, and M. Girolami. 2014. “Langevin Diffusions and the Metropolis-Adjusted Langevin Algorithm.” Statistics & Probability Letters
91 (Supplement C): 14–19.