Diego Mesquita
Diego Mesquita
Getulio Vargas Foundation
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Cited by
Cited by
Rethinking pooling in graph neural networks
D Mesquita, AH Souza, S Kaski
Advances in Neural Information Processing Systems (NeurIPS) 2020, 2020
Euclidean distance estimation in incomplete datasets
DPP Mesquita, JPP Gomes, AH Souza Junior, JS Nobre
Neurocomputing, 2017
Classification with reject option for software defect prediction
DPP Mesquita, LS Rocha, JPP Gomes, ARR Neto
Applied Soft Computing 49, 1085-1093, 2016
Provably expressive temporal graph networks
AH Souza, D Mesquita, S Kaski, V Garg
Advances in Neural Information Processing Systems (NeurIPS) 2022, 2022
Ensemble of efficient minimal learning machines for classification and regression
DPP Mesquita, JPP Gomes, AH Souza Junior
Neural Processing Letters 46, 751-766, 2017
Building selective ensembles of randomization based neural networks with the successive projections algorithm
DPP Mesquita, JPP Gomes, LR Rodrigues, SAF Oliveira, RKH Galvao
Applied Soft Computing 70, 1135-1145, 2018
Federated stochastic gradient Langevin dynamics
KE Mekkaoui, D Mesquita, P Blomstedt, S Kaski
Uncertainty in Artificial Intelligence (UAI) 2021, 2021
Embarrassingly parallel MCMC using deep invertible transformations
D Mesquita, P Blomstedt, S Kaski
Uncertainty in Artificial Intelligence (UAI) 2019, 2019
Gaussian kernels for incomplete data
DPP Mesquita, JPP Gomes, F Corona, AHS Junior, JS Nobre
Applied Soft Computing 77, 356-365, 2019
Pruning extreme learning machines using the successive projections algorithm
DP Mesquita, J Gomes, LR Rodrigues, RK Galvao
IEEE Latin America Transactions 13 (12), 3974-3979, 2015
Ensemble of minimal learning machines for pattern classification
DPP Mesquita, JPP Gomes, AHS Junior
Advances in Computational Intelligence: 13th International Work-Conference …, 2015
Artificial neural networks with random weights for incomplete datasets
DPP Mesquita, JPP Gomes, LR Rodrigues
Neural Processing Letters 50, 2345-2372, 2019
A minimal learning machine for datasets with missing values
DPP Mesquita, JPP Gomes, AHS Jr
Neural Information Processing: 22nd International Conference, ICONIP 2015 …, 2015
LS-SVR as a Bayesian RBF network
DPP Mesquita, LA Freitas, JPP Gomes, CLC Mattos
IEEE Transactions on Neural Networks and Learning Systems 31 (10), 4389-4393, 2019
Fast Co-MLM: An efficient semi-supervised Co-training method based on the minimal learning machine
WL Caldas, JPP Gomes, DPP Mesquita
New Generation Computing 36, 41-58, 2018
A Robust Minimal Learning Machine based on the M-Estimator.
JPP Gomes, DPP Mesquita, A Freire, AHS Júnior, T Kärkkäinen
ESANN, 2017
Distill n'Explain: explaining graph neural networks using simple surrogates
T Pereira, E Nasciment, LE Resck, D Mesquita, A Souza
Artificial Intelligence and Statistics (AISTATS) 2023, 2023
A sparse linear regression model for incomplete datasets
MBA Veras, DPP Mesquita, CLC Mattos, JPP Gomes
Pattern Analysis and Applications 23, 1293-1303, 2020
Shrinkage k-means: a clustering algorithm based on the James-Stein estimator
FFR Damasceno, MBA Veras, DPP Mesquita, JPP Gomes, CEF de Brito
2016 5th Brazilian Conference on Intelligent Systems (BRACIS), 433-437, 2016
Parallel MCMC Without Embarrassing Failures
DA de Souza, D Mesquita, S Kaski, L Acerbi
Artificial Intelligence and Statistics (AISTATS) 2022, 2022
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