Conditional independence testing: a predictive perspective. - Marco Henrique de Almeida Inácio; Rafael Izbicki; Rafael Bassi Stern (CoRR, 2019)

Distance Assessment and Hypothesis Testing of High-Dimensional Samples using Variational Autoencoders. - Marco Henrique de Almeida Inácio; Rafael Izbicki; Bálint Gyires-Tóth (CoRR, 2019)

NLS: an accurate and yet easy-to-interpret regression method. - Victor Coscrato; Marco Henrique de Almeida Inácio; Tiago Botari; Rafael Izbicki (CoRR, 2019)

Simulation studies on Python using sstudy package with SQL databases as storage. - Marco Henrique de Almeida Inácio (CoRR, 2020)

Comparing two populations using Bayesian Fourier series density estimation. - Marco Henrique de Almeida Inácio; Rafael Izbicki; Luis Ernesto Salasar (Commun. Stat. Simul. Comput., 2020)

Bayesian superposition of pure-birth destructive cure processes for tumor latency. - Josemar Rodrigues; Marco Henrique de Almeida Inácio; Adriano K. Suzuki; Fernando Raimundo da Silva; Narayanaswamy Balakrishnan 001 (Commun. Stat. Simul. Comput., 2020)

The NN-Stacking: Feature weighted linear stacking through neural networks. - Victor Coscrato; Marco Henrique de Almeida Inácio; Rafael Izbicki (Neurocomputing, 2020)

Conditional independence testing, two sample comparison and density estimation using neural networks - Marco Henrique de Almeida Inácio (2020)

Distance assessment and analysis of high-dimensional samples using variational autoencoders. - Marco Henrique de Almeida Inácio; Rafael Izbicki; Bálint Gyires-Tóth (Inf. Sci., 2021)

NLS: An accurate and yet easy-to-interpret prediction method. - Victor Coscrato; Marco Henrique de Almeida Inácio; Tiago Botari; Rafael Izbicki (Neural Networks, 2023)