ARTIE and MUSCLE models: building ensemble classifiers from fuzzy ART and SOM networks. - César Lincoln C. Mattos; Guilherme A. Barreto (Neural Comput. Appl., 2013)

Improved Adaline Networks for Robust Pattern Classification. - César Lincoln C. Mattos; José Daniel A. Santos; Guilherme A. Barreto (ICANN, 2014)

A Novel Recursive Kernel-Based Algorithm for Robust Pattern Classification. - José Daniel A. Santos; César Lincoln C. Mattos; Guilherme De A. Barreto (IDEAL, 2014)

An improved hybrid particle swarm optimization algorithm applied to economic modeling of radio resource allocation. - César Lincoln C. Mattos; Guilherme A. Barreto; Francisco Rodrigo P. Cavalcanti (Electron. Commer. Res., 2014)

An Empirical Evaluation of Robust Gaussian Process Models for System Identification. - César Lincoln C. Mattos; José Daniel A. Santos; Guilherme A. Barreto (IDEAL, 2015)

Performance Evaluation of Least Squares SVR in Robust Dynamical System Identification. - José Daniel A. Santos; César Lincoln C. Mattos; Guilherme A. Barreto (IWANN (2), 2015)

Recurrent Gaussian Processes. - César Lincoln C. Mattos; Zhenwen Dai; Andreas C. Damianou; Jeremy Forth; Guilherme A. Barreto; Neil D. Lawrence (ICLR (Poster), 2016)

Randomized Neural Networks for Recursive System Identification in the Presence of Outliers: A Performance Comparison. - César Lincoln C. Mattos; Guilherme A. Barreto; Gonzalo Acuña (IWANN (1), 2017)

Metaheuristic optimization for automatic clustering of customer-oriented supply chain data. - César Lincoln C. Mattos; Guilherme A. Barreto; Dennis Horstkemper; Bernd Hellingrath (WSOM, 2017)

Audio Plugin Recommendation Systems for Music Production. - Paulo Mateus Moura da Silva; César Lincoln Cavalcante Mattos; Amauri Holanda de Souza Júnior (BRACIS, 2019)

Evaluation of Data Based Normal Behavior Models for Fault Detection in Wind Turbines. - Daniel Souza; Thiago de P. Vasconcelos; César L. C. Mattos; João Gomes 002 (BRACIS, 2019)

Sparse minimal learning machine using a diversity measure minimization. - Madson Luiz Dantas Dias; Lucas Silva de Sousa; Ajalmar R. da Rocha Neto; César L. C. Mattos; João P. P. Gomes; Tommi Kärkkäinen (ESANN, 2019)

No-PASt-BO: Normalized Portfolio Allocation Strategy for Bayesian Optimization. - Thiago de P. Vasconcelos; Daniel Augusto R. M. A. de Souza; César L. C. Mattos; João P. P. Gomes (ICTAI, 2019)

OnMLM: An Online Formulation for the Minimal Learning Machine. - Alan L. S. Matias; César L. C. Mattos; Tommi Kärkkäinen; João P. P. Gomes; Ajalmar R. da Rocha Neto (IWANN (1), 2019)

Unscented Gaussian Process Latent Variable Model: learning from uncertain inputs with intractable kernels. - Daniel Augusto R. M. A. de Souza; César Lincoln C. Mattos; João Paulo Pordeus Gomes (CoRR, 2019)

Minimal Learning Machine: Theoretical Results and Clustering-Based Reference Point Selection. - Joonas Hämäläinen; Alisson S. C. Alencar; Tommi Kärkkäinen; César L. C. Mattos; Amauri H. Souza Júnior; João P. P. Gomes (CoRR, 2019)

A stochastic variational framework for Recurrent Gaussian Processes models. - César Lincoln C. Mattos; Guilherme A. Barreto (Neural Networks, 2019)

On the Use of Cultural Enhancement Strategies to Improve the NEAT Algorithm. - Arthur L. A. Paulino; Yuri Lenon Barbosa Nogueira; João P. P. Gomes; César L. C. Mattos; Leonardo Ramos Rodrigues (CEC, 2020)

A New Methodology for Classifying QRS Morphology in ECG Signals. - Weslley L. Caldas; João P. V. Madeiro; César Lincoln C. Mattos; João Paulo Pordeus Gomes (IJCNN, 2020)

Anomaly Detection in Trajectory Data with Normalizing Flows. - Madson L. D. Dias; César Lincoln C. Mattos; Ticiana L. Coelho da Silva; José Antônio Fernandes de Macêdo; Wellington C. P. Silva (IJCNN, 2020)

An Optimized Approach to Huntington's Disease Detecting via Audio Signals Processing with Dimensionality Reduction. - Matheus T. Guimarães; Aldísio Gonçalves Medeiros; Jefferson S. Almeida; Marcos Falcão y Martin; Robertas Damasevicius; Rytis Maskeliunas; César Lincoln Cavalcante Mattos; Pedro Pedrosa Rebouças Filho (IJCNN, 2020)

Detectando Doença de Parkinson - Uma Comparação de Modelos de Aprendizagem de Máquina com Redução de Dimensionalidade Diferencialmente Privada. - Manuel Edvar Bento Filho; Maria de Lourdes Maia Silva; Patrícia Vieira da Silva Barros; César Lincoln Cavalcante Mattos; Javam de Castro Machado (SBBD, 2020)

A sparse linear regression model for incomplete datasets. - Marcelo B. A. Veras; Diego P. P. Mesquita; César Lincoln C. Mattos; João P. P. Gomes (Pattern Anal. Appl., 2020)

LS-SVR as a Bayesian RBF Network. - Diego P. P. Mesquita; Luis A. Freitas; João P. P. Gomes; César L. C. Mattos (IEEE Trans. Neural Networks Learn. Syst., 2020)

Learning GPLVM with arbitrary kernels using the unscented transformation. - Daniel Augusto de Souza; Diego Mesquita; João Paulo Pordeus Gomes; César Lincoln C. Mattos (AISTATS, 2021)

FakeWhastApp.BR: NLP and Machine Learning Techniques for Misinformation Detection in Brazilian Portuguese WhatsApp Messages. - Lucas Cabral 001; José Maria Monteiro; José Wellington Franco da Silva; César Lincoln C. Mattos; Pedro Jorge Chaves Mourão (ICEIS (1), 2021)

A Practical Guide to Support Predictive Tasks in Data Science. - José Augusto Câmara Filho; José Maria Monteiro; César Lincoln C. Mattos; Juvêncio Santos Nobre (ICEIS (1), 2021)

A novel fuzzy ARTMAP with area of influence. - Alan L. S. Matias; Ajalmar R. da Rocha Neto; César Lincoln C. Mattos; João Paulo Pordeus Gomes (Neurocomputing, 2021)

Bayesian Analysis of Bug-Fixing Time using Report Data. - Renan Gomes Vieira; Diego Mesquita; César Lincoln C. Mattos; Ricardo Britto 001; Lincoln S. Rocha; João Gomes 002 (ESEM, 2022)

A Text Classification Methodology to Assist a Large Technical Support System. - Elene Firmeza Ohata; César Lincoln Cavalcante Mattos; Samuel Luz Gomes; Elizângela de S. Rebouças; Paulo Antonio Leal Rego (IEEE Access, 2022)

The role of bug report evolution in reliable fixing estimation. - Renan Gomes Vieira; César Lincoln C. Mattos; Lincoln S. Rocha; João Paulo Pordeus Gomes; Matheus Paixão (Empir. Softw. Eng., 2022)

Self-tuning portfolio-based Bayesian optimization. - Thiago de P. Vasconcelos; Daniel Augusto R. M. A. de Souza; Gustavo C. de M. Virgolino; César L. C. Mattos; João P. P. Gomes (Expert Syst. Appl., 2022)

Evaluating Link Lifetime Prediction to Support Computational Offloading Decision in VANETs. - Paulo Rocha 002; Alisson Barbosa de Souza; Gilvan Maia; César L. C. Mattos; Francisco Airton Silva; Paulo A. L. Rego; Tuan Anh Nguyen 002; Jae-Woo Lee (Sensors, 2022)

Bayesian Multilateration. - Alisson S. C. Alencar; César L. C. Mattos; João P. P. Gomes; Diego Mesquita (IEEE Signal Process. Lett., 2022)

A Vulnerability Risk Assessment Methodology Using Active Learning. - Francisco R. P. da Ponte; Emanuel Bezerra Rodrigues; César L. C. Mattos (AINA (2), 2023)

CVEjoin: An Information Security Vulnerability and Threat Intelligence Dataset. - Francisco R. P. da Ponte; Emanuel Bezerra Rodrigues; César L. C. Mattos (AINA (1), 2023)

Thin and deep Gaussian processes. - Daniel Augusto de Souza; Alexander Nikitin; St John; Magnus Ross; Mauricio A. Álvarez; Marc Peter Deisenroth; João Paulo Pordeus Gomes; Diego Mesquita; César Lincoln C. Mattos (NeurIPS, 2023)

Minimal Learning Machine for Multi-Label Learning. - Joonas Hämäläinen; Amauri H. de Souza; César L. C. Mattos; João P. P. Gomes; Tommi Kärkkäinen (CoRR, 2023)

Amortized Variational Deep Kernel Learning. - Alan L. S. Matias; César Lincoln C. Mattos; João Paulo Pordeus Gomes; Diego Mesquita (ICML, 2024)

Bayesian ART for incomplete datasets. - Alan L. S. Matias; João Paulo Pordeus Gomes; César Lincoln C. Mattos; Ajalmar R. da Rocha Neto; Diego Mesquita (Appl. Soft Comput., 2024)

Edge AI for Internet of Medical Things: A literature review. - Atslands Rego da Rocha; Matheus R. Monteiro; César L. C. Mattos; Madson L. D. Dias; Jorge Barbosa Soares; Regis Pires Magalhães; José A. F. de Macêdo (Comput. Electr. Eng., 2024)

Spatio-temporal wind speed forecasting with approximate Bayesian uncertainty quantification. - Airton F. Souza Neto; César L. C. Mattos; João P. P. Gomes (Neural Comput. Appl., 2024)

Interpretability of Machine Learning Models for Cardiac Arrhythmia Classification. - Bruno Torres Marques; Regis Pires Magalhães; Lívia Almada Cruz; João Paulo do Vale Madeiro; César Lincoln C. Mattos; José A. F. de Macêdo (SBSI, 2025)

FRAPE: A Framework for Risk Assessment, Prioritization and Explainability of vulnerabilities in cybersecurity. - Francisco Rodrigo Parente da Ponte; Emanuel Bezerra Rodrigues; César L. C. Mattos (J. Inf. Secur. Appl., 2025)

AbSet: A Standardized Data Set of Antibody Structures for Machine Learning Applications. - Diego S. Almeida; Matheus V. Almeida; Jean V. Sampaio; Eduardo M. Gaieta; Andrielly H. S. Costa; Francisco F. A. Rabelo; César Lincoln Cavalcante Mattos; Geraldo Rodrigues Sartori; João Herminio Martins Da Silva (J. Chem. Inf. Model., 2025)