Oliver Dunbar

Research Scientist
California Institute of Technology

1200 E. California Blvd.
MC C1-221
Pasadena, CA 91125

odunbar@caltech.edu

Personal website

Biography

Please visit my personal website.

Publications

  • Dunbar, O.R.A., Dunlop, M.M., Elliott, C.M., Hoang, V.H., Stuart, A.M., 2021: Reconciling Bayesian and perimeter regularization for binary inversion. SIAM Journal on Scientific Computing, 42, A1984−A2013.
    [PDF] [Official Version]

  • Dunbar, O.R.A, Duncan, A.B., Stuart, A.M., Wolfram, M.-T., 2022: Ensemble inference methods for models with noisy and expensive likelihoods. SIAM Journal on Applied Dynamical Systems, 21, 1539-1572.
    [PDF] [Official Version]

  • Dunbar, O.R.A., Howland, M.F., Schneider, T., Stuart, A.M., 2022: Ensemble-based experimental design for targeting data requisition to inform climate models. Journal of Advances in Modeling Earth Systems, 14, e2022MS002997.
    [PDF] [Official version]

  • Bieli, M., Dunbar, O.R.A., de Jong, E.K., Jaruga, A., Schneider, T., Bischoff, T., 2022: An efficient Bayesian approach to learning droplet collision kernels: Proof of concept using “Cloudy”, a new n-moment bulk microphysics scheme. Journal of Advances in Modeling Earth Systems, 14, e2022MS002994.
    [PDF] [Official version]

  • Dunbar, O.R.A., Lopez-Gomez, I., Garbuno-Iñigo, A., Huang, D.Z., Bach, E., Wu, J., 2022: EnsembleKalmanProcesses.jl: Derivative-free ensemble-based model calibration. Journal of Open Source Software, 7, 4869.
    [PDF] [Official Version]

  • Lopez-Gomez, I., Christopoulos, C., Langeland Ervik, H.L., Dunbar, O.R.A., Cohen, Y., Schneider, T., 2022: Training physics-based machine-learning parameterizations with gradient-free ensemble Kalman methods. Journal of Advances in Modeling Earth Systems, 14, e2022MS003105.
    [PDF] [Official version]

  • Schneider, T., Dunbar, O.R.A., Wu, J., Böttcher, L., Burov, D., Garbuno-Iñigo, A., Wagner, G.L., Pei, S., Daraio, C., Ferrari, R., Shaman, J., 2022: Epidemic management and control through risk-dependent individual contact interventions. PLOS Computational Biology, 18, e1010171.
    [PDF] [Official Version]

  • Howland, M. F., Dunbar, O. R. A., Schneider, T., 2022: Parameter uncertainty quantification in an idealized GCM with a seasonal cycle, Journal of Advances in Modeling Earth Systems, 14, e2021MS002735.
    [PDF] [Official Version]

  • Dunbar, O. R. A., Garbuno-Inigo, A., Schneider, T., Stuart, A. M., 2021: Calibration and uncertainty quantification of convective parameters in an idealized GCM, Journal of Advances in Modeling Earth Systems, 13, e2020MS002454.
    [PDF] [Official Version]