Reconciling Bayesian and Perimeter Regularization for Binary Inversion. - Oliver R. A. Dunbar; Matthew M. Dunlop; Charles M. Elliott; Viet Ha Hoang; Andrew M. Stuart (SIAM J. Sci. Comput., 2020)

Models for information propagation on graphs. - Oliver R. A. Dunbar; Charles M. Elliott; Lisa Maria Kreusser (CoRR, 2022)

Epidemic management and control through risk-dependent individual contact interventions. - Tapio Schneider; Oliver R. A. Dunbar; Jinlong Wu; Lucas Böttcher; Dmitry Burov; Alfredo Garbuno-Inigo; Gregory LeClaire Wagner; Sen Pei; Chiara Daraio; Raffaele Ferrari; Jeffrey Shaman (PLoS Comput. Biol., 2022)

Ensemble Inference Methods for Models With Noisy and Expensive Likelihoods. - Oliver R. A. Dunbar; Andrew B. Duncan; Andrew M. Stuart; Marie-Therese Wolfram (SIAM J. Appl. Dyn. Syst., 2022)

EnsembleKalmanProcesses.jl: Derivative-free ensemble-based model calibration. - Oliver R. A. Dunbar; Ignacio Lopez-Gomez; Alfredo Garbuno-Iñigo; Daniel Zhengyu Huang; Eviatar Bach; Jinlong Wu (J. Open Source Softw., 2022)

Toward Routing River Water in Land Surface Models with Recurrent Neural Networks. - Mauricio Lima; Katherine Deck; Oliver R. A. Dunbar; Tapio Schneider (CoRR, 2024)

CalibrateEmulateSample.jl: Accelerated Parametric Uncertainty Quantification. - Oliver R. A. Dunbar; Melanie Bieli; Alfredo Garbuno-Iñigo; Michael Howland; Andre Nogueira de Souza; Laura Anne Mansfield; Gregory LeClaire Wagner; N. Efrat-Henrici (J. Open Source Softw., 2024)

Nesterov acceleration for ensemble Kalman inversion and variants. - Sydney Vernon; Eviatar Bach; Oliver R. A. Dunbar (J. Comput. Phys., 2025)

Hyperparameter optimization for randomized algorithms: a case study on random features. - Oliver R. A. Dunbar; Nicholas H. Nelsen; Maya Mutic (Stat. Comput., 2025)