Publications

★ Co-first author.   † Graduate student working under my supervision.

Accepted Manuscripts:
  1. A.C. Murph★, L.J. Beesley★, G.C. Gibson, L.A. Castro, S.Y. Del Valle, and D.A. Osthus (2026). Beyond Equal Weights: A Disease-agnostic Approach to Ensemble Learning for Infectious Disease Forecasting. Accepted to Nature Communications.
  2. A.C. Murph, J.P. Williams, and J. Hannig (2025). Generalized fiducial inference on differentiable manifolds. International Journal of Approximate Reasoning, p.109618, ISSN 0888-613X
  3. A.C. Murph, M.F. Dorn, S. Bhat, A. Nachtsheim, K.J. Kuhn, A.C. Olson, S.M. Andrade, and L. Tandon (2025). Unique and challenging aspects of plutonium metal standards exchange program for actinide measurements. Journal of Radioanalytical and Nuclear Chemistry.
  4. A.C. Murph, G.C. Gibson, L.B. VanDervort, N. Panda, L.A. Castro, S.Y. Del Valle, C.A. Manore, and D.A. Osthus (2025). Mapping incidence and prevalence peak data for SIR forecasting applications. Journal of Mathematical Biology, 91(70).
  5. A.C. Murph★, G.C. Gibson★, E.B. Amona†, L.B. VanDervort, L.A. Castro, S. Y. Del Valle, and D.A. Osthus (2025). Synthetic method of analogues for emerging infectious disease forecasting. PLOS Computational Biology, 21(6): e1013203.
  6. Y. Liu, J. Hannig, and A.C. Murph (2025). A Geometric Perspective on Bayesian and Generalized Fiducial Inference, Statistical Sciences 40(2), 219-234.
  7. J.D. Strait, K.R. Moran, A.C. Murph, J.D. Hyman, H.S. Viswanathan and P. Stauffer (2025). Covariate-informed multi-fidelity bias correction of distributions, Accepted to SIAM/ASA Journal on Uncertainty Quantification.
  8. J.D. Hyman, A.C. Murph, L. Boampong, A. Navarre-Sitchler, G. Srinivasan, J.W. Carey, and H.S. Viswanathan (2024). Determining the dominant factors for carbon mineralization in three-dimensional fracture networks, International Journal of Greenhouse Gas Control, 139, 104-265.
  9. A.C. Murph, J.D. Strait, K.R. Moran, J.D. Hyman, H.S. Viswanathan, and P.H. Stauffer (2024). Sensitivity analysis in the presence of intrinsic stochasticity for discrete fracture network simulations, Journal of Geophysical Research: Machine Learning and Computation, 1, e2023JH000113.
  10. A.C. Murph, J.D. Strait, K.R. Moran, J.D. Hyman, and P.H. Stauffer (2024). Visualisation and outlier detection for probability density function ensembles, Stat, 13(2), e662.
  11. A.C. Murph, J. Hannig, and J.P. Williams (2023). Introduction to generalized fiducial inference. In J. Berger, X. Meng, N. Reid, and M. Xie (Eds.) Handbook of Bayesian, Fiducial, and Frequentist Inference (Ch. 13). Chapman and Hall.
  12. E. Faden, A. Mitchell, A.C. Murph, T. Myers, and N. Ryan (2021). Mr. Hulot’s invisible gorilla: Jacques Tati and inattentional blindness, Projections, 15(2), 1-29.
  13. A.C. Murph, A. Flynt, and B.R. King (2021). Comparing finite sequences of discrete events with non-uniform time intervals, Sequential Analysis, 40(3), 291-313.
Manuscripts in review/preparation:
  • A.C. Murph, C.B. Storlie, P.M. Wilson, J.P. Williams, and J. Hannig (202x). Bayes Watch: Bayesian change-point detection for process monitoring with fault detection, In Review.
  • E.C. Lawrence, A.C. Murph, S.A. Vander Wiel, and C. Liu (202x). A New Method for Multinomial Inference using Dempster-Shafer Theory. In Review.