Towards a Platform for Testing and Developing Privacy-Preserving Data Mining Applications for Smart Grids. - Andrew Koster; Gabriel de Oliveira Ramos; Ana L. C. Bazzan; Fernando Koch (MATES, 2013)

Self-Adapting Coalition Formation Among Electric Vehicles in Smart Grids. - Gabriel de Oliveira Ramos; Juan C. Burguillo-Rial; Ana L. C. Bazzan (SASO, 2013)

An Improved Learning Automata Approach for the Route Choice Problem. - Gabriel de Oliveira Ramos; Ricardo Grunitzki (ARE/AVSA@AAMAS, 2014)

Individual versus Difference Rewards on Reinforcement Learning for Route Choice. - Ricardo Grunitzki; Gabriel de Oliveira Ramos; Ana Lúcia C. Bazzan (BRACIS, 2014)

Dynamic constrained coalition formation among electric vehicles. - Gabriel de Oliveira Ramos; Juan C. Burguillo; Ana L. C. Bazzan (J. Braz. Comput. Soc., 2014)

Towards the User Equilibrium in Traffic Assignment Using GRASP with Path Relinking. - Gabriel de Oliveira Ramos; Ana Lúcia Cetertich Bazzan (GECCO, 2015)

Forming Coalitions of Electric Vehicles in Constrained Scenarios. - Ana L. C. Bazzan; Gabriel de Oliveira Ramos (PAAMS (Workshops), 2015)

A self-adapting similarity-based coalition formation approach for plug-in electric vehicles in smart grids. - Gabriel de Oliveira Ramos; Juan C. Burguillo; Ana L. C. Bazzan (Multiagent Grid Syst., 2015)

Efficient local search in traffic assignment. - Gabriel de Oliveira Ramos; Ana L. C. Bazzan (CEC, 2016)

On Estimating Action Regret and Learning From It in Route Choice. - Gabriel de Oliveira Ramos; Ana L. C. Bazzan (ATT@IJCAI, 2016)

Minimising Regret in Route Choice. - Gabriel de Oliveira Ramos (AAMAS, 2017)

Learning to Minimise Regret in Route Choice. - Gabriel de Oliveira Ramos; Bruno Castro da Silva; Ana L. C. Bazzan (AAMAS, 2017)

Self-Adaptive Appearance-Based Eye-Tracking with Online Transfer Learning. - Bruno Klein Salvalaio; Gabriel de Oliveira Ramos (BRACIS, 2019)

Experience Sharing Between Cooperative Reinforcement Learning Agents. - Lucas Oliveira Souza; Gabriel de Oliveira Ramos; Célia Ghedini Ralha (ICTAI, 2019)

Toll-Based Learning for Minimising Congestion under Heterogeneous Preferences. - Gabriel de Oliveira Ramos; Roxana Radulescu; Ann Nowé; Anderson R. Tavares (AAMAS, 2020)

On the Role of Reward Functions for Reinforcement Learning in the Traffic Assignment Problem. - Ricardo Grunitzki; Gabriel de Oliveira Ramos (IJCNN, 2020)

Binary Segmentation of Seismic Facies Using Encoder-Decoder Neural Networks. - Gefersom Lima; Gabriel de Oliveira Ramos; Sandro Rigo; Felipe André Zeiser; Ariane da Silveira (CoRR, 2020)

ElHealth: Using Internet of Things and data prediction for elastic management of human resources in smart hospitals. - Gabriel Souto Fischer; Rodrigo da Rosa Righi; Gabriel de Oliveira Ramos; Cristiano André da Costa; Joel J. P. C. Rodrigues (Eng. Appl. Artif. Intell., 2020)

Toll-based reinforcement learning for efficient equilibria in route choice. - Gabriel de Oliveira Ramos; Bruno C. da Silva 001; Roxana Radulescu; Ana L. C. Bazzan; Ann Nowé (Knowl. Eng. Rev., 2020)

An Enhanced TSP-Based Approach for Active Debris Removal Mission Planning. - João Batista Rodrigues Neto; Gabriel de Oliveira Ramos (BRACIS (1), 2021)

Evaluation of Convolutional Neural Networks for COVID-19 Classification on Chest X-Rays. - Felipe André Zeiser; Cristiano André da Costa; Gabriel de Oliveira Ramos; Henrique Bohn; Ismael Santos 002; Rodrigo da Rosa Righi (BRACIS (2), 2021)

Fuzzy time series for predicting phenological stages of apple trees. - Tiago Boechel; Lucas Micol Policarpo; Gabriel de Oliveira Ramos; Rodrigo da Rosa Righi (SAC, 2021)

HealthMon: An approach for monitoring machines degradation using time-series decomposition, clustering, and metaheuristics. - Miromar José de Lima; César David Paredes Crovato; Rodrigo Ivan Goytia Mejia; Rodrigo da Rosa Righi; Gabriel de Oliveira Ramos; Cristiano André da Costa; Giovani Pesenti (Comput. Ind. Eng., 2021)

A feature identification method to explain anomalies in condition monitoring. - Marcos Leandro Hoffmann Souza; Cristiano André da Costa; Gabriel de Oliveira Ramos; Rodrigo da Rosa Righi (Comput. Ind., 2021)

DeepBatch: A hybrid deep learning model for interpretable diagnosis of breast cancer in whole-slide images. - Felipe André Zeiser; Cristiano André da Costa; Gabriel de Oliveira Ramos; Henrique Bohn; Ismael Santos 002; Adriana Vial Roehe (Expert Syst. Appl., 2021)

A systematic mapping study of robotics in human care. - Nícolas B. Santos; Rodrigo Simon Bavaresco; João Elison da Rosa Tavares; Gabriel de Oliveira Ramos; Jorge L. V. Barbosa (Robotics Auton. Syst., 2021)

On Social Consensus Mechanisms for Federated Learning Aggregation. - Igor Felipe de Camargo; Rodolfo Stoffel Antunes; Gabriel de Oliveira Ramos (BRACIS (2), 2022)

Aiding Glaucoma Diagnosis from the Automated Classification and Segmentation of Fundus Images. - Lucas M. Ceschini; Lucas Micol Policarpo; Rodrigo da Rosa Righi; Gabriel de Oliveira Ramos (BRACIS (2), 2022)

Multi-objective prioritization for data center vulnerability remediation. - Felipe Colombelli; Vítor Kehl Matter; Bruno Iochins Grisci; Leomar Lima; Karine Heinen; Marcio Borges; Sandro José Rigo; Jorge Luis Victória Barbosa; Rodrigo da Rosa Righi; Cristiano André da Costa; Gabriel de Oliveira Ramos (CEC, 2022)

An Interpolated Approach for Active Debris Removal. - João Batista Rodrigues Neto; Gabriel de Oliveira Ramos (CEC, 2022)

The multi-objective dynamic shortest path problem. - Juarez Machado da Silva; Gabriel de Oliveira Ramos; Jorge L. V. Barbosa (CEC, 2022)

A Machine Learning Pipeline for Extracting Decision-Support Features from Traffic Scenes. - Vitor A. Fraga; Lincoln Schreiber; Rafael Kunst; Jorge L. V. Barbosa; Gabriel de Oliveira Ramos (ATT@IJCAI, 2022)

DeepCADD: A Deep Learning Architecture for Automatic Detection of Coronary Artery Disease. - Samuel A. Freitas; Felipe André Zeiser; Cristiano André da Costa; Gabriel de Oliveira Ramos (IJCNN, 2022)

On the Explainability and Expressiveness of Function Approximation Methods in RL-Based Traffic Signal Control. - Lincoln Vinicius Schreiber; Lucas Nunes Alegre; Ana L. C. Bazzan; Gabriel de Oliveira Ramos (IJCNN, 2022)

MoStress: a Sequence Model for Stress Classification. - Arturo de Souza; Mateus Begnini Melchiades; Sandro José Rigo; Gabriel de Oliveira Ramos (IJCNN, 2022)

A practical guide to multi-objective reinforcement learning and planning. - Conor F. Hayes; Roxana Radulescu; Eugenio Bargiacchi; Johan Källström; Matthew Macfarlane; Mathieu Reymond; Timothy Verstraeten; Luisa M. Zintgraf; Richard Dazeley; Fredrik Heintz; Enda Howley; Athirai A. Irissappane; et al. (Auton. Agents Multi Agent Syst., 2022)

Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). - Peter Vamplew 001; Benjamin J. Smith; Johan Källström; Gabriel de Oliveira Ramos; Roxana Radulescu; Diederik M. Roijers; Conor F. Hayes; Fredrik Heintz; Patrick Mannion; Pieter J. K. Libin; Richard Dazeley; Cameron Foale (Auton. Agents Multi Agent Syst., 2022)

Prediction of Harvest Time of Apple Trees: An RNN-Based Approach. - Tiago Boechel; Lucas Micol Policarpo; Gabriel de Oliveira Ramos; Rodrigo da Rosa Righi; Dhananjay Singh 001 (Algorithms, 2022)

A rapid review of machine learning approaches for telemedicine in the scope of COVID-19. - Luana Carine Schünke; Blanda Mello; Cristiano André da Costa; Rodolfo Stoffel Antunes; Sandro José Rigo; Gabriel de Oliveira Ramos; Rodrigo da Rosa Righi; Juliana Nichterwitz Scherer; Bruna Donida (Artif. Intell. Medicine, 2022)

Perspectives on risk prioritization of data center vulnerabilities using rank aggregation and multi-objective optimization. - Bruno Grisci; Gabriela Kuhn; Felipe Colombelli; Vítor Kehl Matter; Leomar Lima; Karine Heinen; Mauricio Pegoraro; Marcio Borges; Sandro José Rigo; Jorge L. V. Barbosa; Rodrigo da Rosa Righi; Cristiano André da Costa; et al. (CoRR, 2022)

ELFpm: A machine learning framework for industrial machines prediction of remaining useful life. - Jovani Dalzochio; Rafael Kunst; Jorge Luis Victória Barbosa; Henrique Damasceno Vianna; Gabriel de Oliveira Ramos; Edison Pignaton; Alécio P. D. Binotto; Jose Favilla (Neurocomputing, 2022)

Scalar Reward is Not Enough. - Peter Vamplew 001; Benjamin J. Smith; Johan Källström; Gabriel de Oliveira Ramos; Roxana Radulescu; Diederik M. Roijers; Conor F. Hayes; Friedrik Hentz; Patrick Mannion; Pieter J. K. Libin; Richard Dazeley; Cameron Foale (AAMAS, 2023)

A Brief Guide to Multi-Objective Reinforcement Learning and Planning. - Conor F. Hayes; Roxana Radulescu; Eugenio Bargiacchi; Johan Källström; Matthew Macfarlane; Mathieu Reymond; Timothy Verstraeten; Luisa M. Zintgraf; Richard Dazeley; Fredrik Heintz; Enda Howley; Athirai A. Irissappane; et al. (AAMAS, 2023)

Pleural Effusion Classification on Chest X-Ray Images with Contrastive Learning. - Felipe André Zeiser; Ismael Santos 002; Henrique Bohn; Cristiano André da Costa; Gabriel de Oliveira Ramos; Rodrigo da Rosa Righi; Andreas Maier 001; José Rodrigo M. Andrade; Alexandre Bacelar (WEBIST, 2023)

Multi-Objective Decision-Making Meets Dynamic Shortest Path: Challenges and Prospects. - Juarez Machado da Silva; Gabriel de Oliveira Ramos; Jorge Luis Victória Barbosa (Algorithms, 2023)

A machine-learning based data-oriented pipeline for Prognosis and Health Management Systems. - Marcos Leandro Hoffmann Souza; Cristiano André da Costa; Gabriel de Oliveira Ramos (Comput. Ind., 2023)

Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. - Peter Vamplew 001; Cameron Foale; Conor F. Hayes; Patrick Mannion; Enda Howley; Richard Dazeley; Scott Johnson; Johan Källström; Gabriel de Oliveira Ramos; Roxana Radulescu; Willem Röpke; Diederik M. Roijers (AAMAS, 2024)

Enhancing Synthetic Well Logs with PCA-Based GAN Models. - Luciano Garim Garcia; Gabriel de Oliveira Ramos; José Manuel Marques Teixeira de Oliveira; Ariane da Silveira (ICMLA, 2024)

A machine learning pipeline for extracting decision-support features from traffic scenes. - Vitor A. Fraga; Lincoln Vinicius Schreiber; Marco Antonio Chitolina Da Silva; Rafael Kunst; Jorge L. V. Barbosa; Gabriel de Oliveira Ramos (AI Commun., 2024)

CheXReport: A transformer-based architecture to generate chest X-ray reports suggestions. - Felipe André Zeiser; Cristiano André da Costa; Gabriel de Oliveira Ramos; Andreas K. Maier; Rodrigo da Rosa Righi (Expert Syst. Appl., 2024)

Advancing Chatbot Conversations: A Review of Knowledge Update Approaches. - Luis Antonio Leite Francisco da Costa; Mateus Begnini Melchiades; Valéria Soldera Girelli; Felipe Colombelli; Denis A. de Araujo; Sandro José Rigo; Gabriel de Oliveira Ramos; Cristiano André da Costa; Rodrigo da Rosa Righi; Jorge Luis Victória Barbosa (J. Braz. Comput. Soc., 2024)

Detecção de Emoções na Aprendizagem de Programação: Os Efeitos de Usar Estimativas de Conhecimento em Modelos Livres de Sensores que Detectam a Confusão do Aluno. - Tiago Roberto Kautzmann; Gabriel de Oliveira Ramos; Patrícia A. Jaques (Revista Brasileira de Informática na Educ., 2024)

UnbIAs - Google Translate Gender Bias Mitigation and Addition of Genderless Translation. - Vanessa Schenkel; Blanda Mello; Sandro José Rigo; Gabriel de Oliveira Ramos (RITA, 2024)

An encoder-decoder deep neural network for binary segmentation of seismic facies. - Gefersom Lima; Felipe André Zeiser; Ariane da Silveira; Sandro José Rigo; Gabriel de Oliveira Ramos (Comput. Geosci., 2024)

Scaling laws in zero-shot gender classification using CLIP. - Lucas M. Ceschini; Gabriel de Oliveira Ramos; Cláudio R. Jung (CVPR Workshops, 2025)

Dynamic Option Creation in Option-Critic Reinforcement Learning. - Mateus Begnini Melchiades; Gabriel de Oliveira Ramos; Bruno C. da Silva 001 (AAMAS, 2025)

Analytical propagation of errors and uncertainties in deep neural networks in the domain of physical sciences. - Gerson Eduardo de Mello; Vitor Camargo Nardelli; Rodrigo da Rosa Righi; Luiz Schirmer; Gabriel de Oliveira Ramos (Eng. Appl. Artif. Intell., 2025)