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Brieuc Lehmann
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2020 – today
- 2024
- [j4]Brieuc Lehmann, Simon R. White
:
A Bayesian multilevel model for populations of networks using exponential-family random graphs. Stat. Comput. 34(4): 136 (2024) - 2023
- [j3]Robin Mitra
Learning from data with structured missingness. Nat. Mac. Intell. 5(1): 13-23 (2023) - [c3]Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong, Brieuc Lehmann:
Quasi-Bayesian nonparametric density estimation via autoregressive predictive updates. UAI 2023: 658-668 - [i3]Robin Mitra, Sarah F. McGough, Tapabrata Chakraborti, Chris C. Holmes, Ryan Copping, Niels Hagenbuch, Stefanie Biedermann, Jack Noonan, Brieuc Lehmann, Aditi Shenvi, Xuan Vinh Doan, David Leslie, Ginestra Bianconi, Rubén J. Sánchez-García, Alisha Davies, Maxine Mackintosh, Eleni-Rosalina Andrinopoulou, Anahid Basiri, Chris Harbron, Ben D. MacArthur:
Learning from data with structured missingness. CoRR abs/2304.01429 (2023) - 2022
- [c2]Edwin Fong, Brieuc Lehmann:
A Predictive Approach to Bayesian Nonparametric Survival Analysis. AISTATS 2022: 6990-7013 - [c1]Oscar Clivio, Fabian Falck, Brieuc Lehmann, George Deligiannidis, Chris C. Holmes:
Neural score matching for high-dimensional causal inference. AISTATS 2022: 7076-7110 - [i2]Oscar Clivio, Fabian Falck, Brieuc Lehmann, George Deligiannidis
Neural Score Matching for High-Dimensional Causal Inference. CoRR abs/2203.00554 (2022) - [i1]Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong
Density Estimation with Autoregressive Bayesian Predictives. CoRR abs/2206.06462 (2022) - 2021
- [j2]B. C. L. Lehmann
Characterising group-level brain connectivity: A framework using Bayesian exponential random graph models. NeuroImage 225: 117480 (2021)
2010 – 2019
- 2017
- [j1]B. C. L. Lehmann
Assessing dynamic functional connectivity in heterogeneous samples. NeuroImage 157: 635-647 (2017)
Coauthor Index
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