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Journal Articles
- 2024
[j7]Aki Vehtari, Daniel Simpson, Andrew Gelman, Yuling Yao, Jonah Gabry:
Pareto Smoothed Importance Sampling. J. Mach. Learn. Res. 25: 72:1-72:58 (2024)- [j6]Alex Cooper, Aki Vehtari
, Catherine Forbes, Daniel Simpson, Lauren Kennedy:
Bayesian cross-validation by parallel Markov chain Monte Carlo. Stat. Comput. 34(4): 119 (2024) - 2023
- [j5]Joaquín Martínez-Minaya, Finn Lindgren, Antonio López-Quílez, Daniel Simpson, David V. Conesa:
The Integrated Nested Laplace Approximation for Fitting Dirichlet Regression Models. J. Comput. Graph. Stat. 32(3): 805-823 (2023) - 2017
- [j4]Andrew Gelman, Daniel Simpson, Michael Betancourt:
The Prior Can Often Only Be Understood in the Context of the Likelihood. Entropy 19(10): 555 (2017) - 2013
- [j3]Thiago G. Martins, Daniel Simpson, Finn Lindgren, Håvard Rue:
Bayesian computing with INLA: New features. Comput. Stat. Data Anal. 67: 68-83 (2013) - [j2]Åke Brännström, Linus Carlsson, Daniel Simpson:
On the Convergence of the Escalator Boxcar Train. SIAM J. Numer. Anal. 51(6): 3213-3231 (2013) - 2012
- [j1]Charles A. Cusack, Timothy Lewis, Daniel Simpson, Samuel Taggart:
The Complexity of Pebbling in Diameter Two Graphs. SIAM J. Discret. Math. 26(3): 919-928 (2012)
Conference and Workshop Papers
- 2024
- [c4]Quincy Card, Daniel Simpson, Kshitiz Aryal, Maanak Gupta, Sheikh Rabiul Islam:
Explainable Deep Learning Models for Dynamic and Online Malware Classification. SMARTCOMP 2024: 182-189 - 2020
- [c3]Alexander Terenin, Daniel Simpson, David Draper:
Asynchronous Gibbs Sampling. AISTATS 2020: 144-154 - [c2]Charles C. Margossian, Aki Vehtari, Daniel Simpson, Raj Agrawal:
Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond. NeurIPS 2020 - 2018
- [c1]Yuling Yao, Aki Vehtari, Daniel Simpson, Andrew Gelman:
Yes, but Did It Work?: Evaluating Variational Inference. ICML 2018: 5577-5586
Informal and Other Publications
- 2024
- [i3]Quincy Card, Daniel Simpson, Kshitiz Aryal, Maanak Gupta, Sheikh Rabiul Islam:
Explainable Deep Learning Models for Dynamic and Online Malware Classification. CoRR abs/2404.12473 (2024) - [i2]Samuel Duffield, Kaelan Donatella, Johnathan Chiu, Phoebe Klett, Daniel Simpson:
Scalable Bayesian Learning with posteriors. CoRR abs/2406.00104 (2024) - 2023
- [i1]Maxwell Aifer, Kaelan Donatella, Max Hunter Gordon, Thomas Ahle, Daniel Simpson, Gavin E. Crooks, Patrick J. Coles:
Thermodynamic Linear Algebra. CoRR abs/2308.05660 (2023)
Coauthor Index
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