Bayesian inference for generalized extreme value distributions via Hamiltonian Monte Carlo. - Marcelo Hartmann; Ricardo S. Ehlers (Commun. Stat. Simul. Comput., 2017)

Prior specification via prior predictive matching: Poisson matrix factorization and beyond. - Eliezer de Souza da Silva; Tomasz Kusmierczyk; Marcelo Hartmann; Arto Klami (CoRR, 2019)

A Bernoulli autoregressive moving average model applied to rainfall occurrence. - Eder Angelo Milani; Marcelo Hartmann; Marinho Gomes Andrade; Carlos Alberto Ribeiro Diniz (Commun. Stat. Simul. Comput., 2019)

Laplace approximation and natural gradient for Gaussian process regression with heteroscedastic student-t model. - Marcelo Hartmann; Jarno Vanhatalo (Stat. Comput., 2019)

Flexible Prior Elicitation via the Prior Predictive Distribution. - Marcelo Hartmann; Georgi Agiashvili; Paul C. Bürkner; Arto Klami (UAI, 2020)

Lagrangian manifold Monte Carlo on Monge patches. - Marcelo Hartmann; Mark Girolami; Arto Klami (AISTATS, 2022)

Transformed Gaussian Processes for Characterizing a Model's Discrepancy. - Aurélien Nioche; Ville Tanskanen; Marcelo Hartmann; Arto Klami (ACML, 2023)

Warped geometric information on the optimisation of Euclidean functions. - Marcelo Hartmann; Bernardo Williams; Hanlin Yu; Mark Girolami; Alessandro Barp; Arto Klami (CoRR, 2023)

Prior Specification for Bayesian Matrix Factorization via Prior Predictive Matching. - Eliezer de Souza da Silva; Tomasz Kusmierczyk; Marcelo Hartmann; Arto Klami (J. Mach. Learn. Res., 2023)

Scalable Stochastic Gradient Riemannian Langevin Dynamics in Non-Diagonal Metrics. - Hanlin Yu; Marcelo Hartmann; Bernardo Williams; Arto Klami (Trans. Mach. Learn. Res., 2023)

Riemannian Laplace Approximation with the Fisher Metric. - Hanlin Yu; Marcelo Hartmann; Bernardo Williams Moreno Sanchez; Mark Girolami; Arto Klami (AISTATS, 2024)

Non-geodesically-convex optimization in the Wasserstein space. - Hoang Phuc Hau Luu; Hanlin Yu; Bernardo Williams; Petrus Mikkola; Marcelo Hartmann; Kai Puolamäki; Arto Klami (NeurIPS, 2024)

Geometric No-U-Turn Samplers: Concepts and Evaluation. - Bernardo Williams; Hanlin Yu; Marcelo Hartmann; Arto Klami (PGM, 2024)

Stochastic variance-reduced Gaussian variational inference on the Bures-Wasserstein manifold. - Hoang Phuc Hau Luu; Hanlin Yu; Bernardo Williams; Marcelo Hartmann; Arto Klami (ICLR, 2025)

Learning geometry and topology via multi-chart flows. - Hanlin Yu; Søren Hauberg; Marcelo Hartmann; Arto Klami; Georgios Arvanitidis (CoRR, 2025)