default search action
Diego Parente Paiva Mesquita
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
- [j12]Alan L. S. Matias, João Paulo Pordeus Gomes, César Lincoln C. Mattos, Ajalmar R. da Rocha Neto, Diego Mesquita:
Bayesian ART for incomplete datasets. Appl. Soft Comput. 163: 111865 (2024) - [j11]Antônio da Silva, Renan Gomes Vieira, Diego P. P. Mesquita, João Paulo Pordeus Gomes, Lincoln S. Rocha:
Towards automatic labeling of exception handling bugs: A case study of 10 years bug-fixing in Apache Hadoop. Empir. Softw. Eng. 29(4): 85 (2024) - [c23]Alan L. S. Matias, César Lincoln C. Mattos, João Paulo Pordeus Gomes, Diego Mesquita:
Amortized Variational Deep Kernel Learning. ICML 2024 - [c22]Tiago da Silva, Luiz Max Carvalho, Amauri H. Souza, Samuel Kaski, Diego Mesquita:
Embarrassingly Parallel GFlowNets. ICML 2024 - [i12]Erik Nascimento, Diego Mesquita, Samuel Kaski, Amauri H. Souza:
In-n-Out: Calibrating Graph Neural Networks for Link Prediction. CoRR abs/2403.04605 (2024) - [i11]Tiago da Silva, Luiz Max Carvalho, Amauri H. Souza, Samuel Kaski, Diego Mesquita:
Embarrassingly Parallel GFlowNets. CoRR abs/2406.03288 (2024) - 2023
- [c21]Tamara A. Pereira, Erik Nascimento, Lucas E. Resck, Diego Mesquita, Amauri H. Souza:
Distill n' Explain: explaining graph neural networks using simple surrogates. AISTATS 2023: 6199-6214 - [c20]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:
Thin and deep Gaussian processes. NeurIPS 2023 - [i10]Tamara A. Pereira, Erik Nascimento, Lucas E. Resck, Diego Mesquita, Amauri H. Souza:
Distill n' Explain: explaining graph neural networks using simple surrogates. CoRR abs/2303.10139 (2023) - [i9]Yuling Yao, Luiz Max Carvalho, Diego Mesquita, Yann McLatchie:
Locking and Quacking: Stacking Bayesian model predictions by log-pooling and superposition. CoRR abs/2305.07334 (2023) - [i8]Tiago da Silva, Eliezer S. Silva, Adèle H. Ribeiro, António Góis, Dominik Heider, Samuel Kaski, Diego Mesquita:
Human-in-the-Loop Causal Discovery under Latent Confounding using Ancestral GFlowNets. CoRR abs/2309.12032 (2023) - [i7]Daniel Augusto de Souza, Alexander Nikitin, St John, Magnus Ross, Mauricio A. Álvarez, Marc Peter Deisenroth, João P. P. Gomes, Diego Mesquita, César Lincoln C. Mattos:
Thin and Deep Gaussian Processes. CoRR abs/2310.11527 (2023) - 2022
- [j10]Alisson S. C. Alencar, César L. C. Mattos, João P. P. Gomes, Diego Mesquita:
Bayesian Multilateration. IEEE Signal Process. Lett. 29: 962-966 (2022) - [c19]Daniel Augusto de Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi:
Parallel MCMC Without Embarrassing Failures. AISTATS 2022: 1786-1804 - [c18]Tamara A. Pereira, Erik Jhones F. do Nascimento, Diego Mesquita, Amauri H. Souza:
ConveXplainer for Graph Neural Networks. BRACIS (2) 2022: 588-600 - [c17]Renan Gomes Vieira, Diego Mesquita, César Lincoln C. Mattos, Ricardo Britto, Lincoln S. Rocha, João Gomes:
Bayesian Analysis of Bug-Fixing Time using Report Data. ESEM 2022: 57-68 - [c16]Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg:
Provably expressive temporal graph networks. NeurIPS 2022 - [i6]Daniel Augusto de Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi:
Parallel MCMC Without Embarrassing Failures. CoRR abs/2202.11154 (2022) - [i5]Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg:
Provably expressive temporal graph networks. CoRR abs/2209.15059 (2022) - 2021
- [b1]Diego Mesquita:
Advances in distributed Bayesian inference and graph neural networks. Aalto University, Espoo, Finland, 2021 - [c15]Daniel Augusto de Souza, Diego P. P. Mesquita, João Paulo Pordeus Gomes, César Lincoln C. Mattos:
Learning GPLVM with arbitrary kernels using the unscented transformation. AISTATS 2021: 451-459 - [c14]Erik Jhones F. do Nascimento, Amauri H. Souza, Diego Mesquita:
Improving Graph Variational Autoencoders with Multi-Hop Simple Convolutions. ESANN 2021 - [c13]Khaoula el Mekkaoui, Diego Mesquita, Paul Blomstedt, Samuel Kaski:
Federated stochastic gradient Langevin dynamics. UAI 2021: 1703-1712 - 2020
- [j9]Marcelo B. A. Veras, Diego P. P. Mesquita, César Lincoln C. Mattos, João P. P. Gomes:
A sparse linear regression model for incomplete datasets. Pattern Anal. Appl. 23(3): 1293-1303 (2020) - [j8]Diego P. P. Mesquita, Luis A. Freitas, João P. P. Gomes, César L. C. Mattos:
LS-SVR as a Bayesian RBF Network. IEEE Trans. Neural Networks Learn. Syst. 31(10): 4389-4393 (2020) - [c12]Diego P. P. Mesquita, Amauri H. Souza Jr., Samuel Kaski:
Rethinking pooling in graph neural networks. NeurIPS 2020 - [i4]Khaoula el Mekkaoui, Diego P. P. Mesquita, Paul Blomstedt, Samuel Kaski:
Variance reduction for distributed stochastic gradient MCMC. CoRR abs/2004.11231 (2020) - [i3]Diego P. P. Mesquita, Amauri H. Souza Jr., Samuel Kaski:
Rethinking pooling in graph neural networks. CoRR abs/2010.11418 (2020)
2010 – 2019
- 2019
- [j7]Diego P. P. Mesquita, João P. P. Gomes, Francesco Corona, Amauri Holanda de Souza Júnior, Juvêncio S. Nobre:
Gaussian kernels for incomplete data. Appl. Soft Comput. 77: 356-365 (2019) - [j6]Diego P. P. Mesquita, João Paulo Pordeus Gomes, Leonardo Ramos Rodrigues:
Artificial Neural Networks with Random Weights for Incomplete Datasets. Neural Process. Lett. 50(3): 2345-2372 (2019) - [c11]Diego P. P. Mesquita, Paul Blomstedt, Samuel Kaski:
Embarrassingly Parallel MCMC using Deep Invertible Transformations. UAI 2019: 1244-1252 - [i2]Diego P. P. Mesquita, Paul Blomstedt, Samuel Kaski:
Embarrassingly parallel MCMC using deep invertible transformations. CoRR abs/1903.04556 (2019) - [i1]Diego P. P. Mesquita, Luis A. Freitas, João P. P. Gomes, César L. C. Mattos:
LS-SVR as a Bayesian RBF network. CoRR abs/1905.00332 (2019) - 2018
- [j5]Diego P. P. Mesquita, João Paulo Pordeus Gomes, Leonardo Ramos Rodrigues, Saulo A. F. Oliveira, Roberto Kawakami Harrop Galvão:
Building selective ensembles of Randomization Based Neural Networks with the successive projections algorithm. Appl. Soft Comput. 70: 1135-1145 (2018) - [j4]Weslley L. Caldas, João P. P. Gomes, Diego P. P. Mesquita:
Fast Co-MLM: An Efficient Semi-supervised Co-training Method Based on the Minimal Learning Machine. New Gener. Comput. 36(1): 41-58 (2018) - 2017
- [j3]Diego Parente Paiva Mesquita, João P. P. Gomes, Amauri Holanda Souza Júnior, Juvêncio Santos Nobre:
Euclidean distance estimation in incomplete datasets. Neurocomputing 248: 11-18 (2017) - [j2]Diego P. P. Mesquita, João P. P. Gomes, Amauri Holanda de Souza Júnior:
Ensemble of Efficient Minimal Learning Machines for Classification and Regression. Neural Process. Lett. 46(3): 751-766 (2017) - [c10]João P. P. Gomes, Diego P. P. Mesquita, Ananda Freire, Amauri H. Souza Júnior, Tommi Kärkkäinen:
A Robust Minimal Learning Machine based on the M-Estimator. ESANN 2017 - [c9]Marcelo B. A. Veras, Diego P. P. Mesquita, João P. P. Gomes, Amauri H. Souza Júnior, Guilherme A. Barreto:
Forward Stagewise Regression on Incomplete Datasets. IWANN (1) 2017: 386-395 - 2016
- [j1]Diego Parente Paiva Mesquita, Lincoln S. Rocha, João P. P. Gomes, Ajalmar R. da Rocha Neto:
Classification with reject option for software defect prediction. Appl. Soft Comput. 49: 1085-1093 (2016) - [c8]Diego Parente Paiva Mesquita, João Paulo Pordeus Gomes, Leonardo Ramos Rodrigues:
Extreme Learning Machines for Datasets with Missing Values Using the Unscented Transform. BRACIS 2016: 85-90 - [c7]Weslley L. Caldas, João Paulo Pordeus Gomes, Michelle G. Cacais, Diego Parente Paiva Mesquita:
Co-MLM: A SSL Algorithm Based on the Minimal Learning Machine. BRACIS 2016: 97-102 - [c6]Filipe F. R. Damasceno, Marcelo B. A. Veras, Diego Parente Paiva Mesquita, João Paulo Pordeus Gomes, Carlos Eduardo Fisch de Brito:
Shrinkage k-Means: A Clustering Algorithm Based on the James-Stein Estimator. BRACIS 2016: 433-437 - [c5]Diego P. P. Mesquita, João P. P. Gomes, Leonardo Ramos Rodrigues:
K-means for Datasets with Missing Attributes: Building Soft Constraints with Observed and Imputed Values. ESANN 2016 - [c4]Diego P. P. Mesquita, Antônio C. Araújo Neto, Jose Queiroz Neto, João P. P. Gomes, Leonardo Ramos Rodrigues:
Using Robust Extreme Learning Machines to Predict Cotton Yarn Strength and Hairiness. ESANN 2016 - [c3]Diego Parente Paiva Mesquita, João Paulo Pordeus Gomes:
Radial Basis Function Neural Networks for Datasets with Missing Values. ISDA 2016: 108-115 - 2015
- [c2]Diego Parente Paiva Mesquita, João Paulo Pordeus Gomes, Amauri H. Souza Jr.:
A Minimal Learning Machine for Datasets with Missing Values. ICONIP (1) 2015: 565-572 - [c1]Diego Parente Paiva Mesquita, João Paulo Pordeus Gomes, Amauri Holanda Souza Júnior:
Ensemble of Minimal Learning Machines for Pattern Classification. IWANN (2) 2015: 142-152
Coauthor Index
aka: César L. C. Mattos
aka: Amauri Holanda de Souza Júnior
aka: Amauri Holanda Souza Júnior
aka: Amauri H. Souza Júnior
aka: Amauri H. Souza Jr.
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from , , and to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-22 19:45 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint