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João M. Pereira

Orcid: 0000-0003-3773-7623

Affiliations:

Instituto de Matemática Pura e Aplicada (IMPA), Rio de Janeiro, RJ, Brazil
University of Texas at Austin, Oden Institute for Computational Sciences, Austin, TX, USA (former)
Duke University, Department of Electrical and Computer Engineering, Durham, NC, USA (former)
Princeton University, The Program in Applied and Computational Mathematics, NJ, USA (former, PhD 2019)

According to our database¹, João M. Pereira authored at least 15 papers between 2017 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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Online presence:

On csauthors.net:

Bibliography

2025

Neural Conjugate Flows: A Physics-Informed Architecture with Flow Structure.

[BibT_eX]

[DOI]

,

Lucas Nissenbaum

,

João M. Pereira

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

A Search-Free \({O(1/{k}^{3/2})}\) Homotopy Inexact Proximal-Newton Extragradient Algorithm for Monotone Variational Inequalities.

[BibT_eX]

[DOI]

Maicon Marques Alves

,

João M. Pereira

,

Benar Fux Svaiter

SIAM J. Optim., 2024

Neural Conjugate Flows: Physics-informed architectures with flow structure.

[BibT_eX]

[DOI]

,

Lucas Nissenbaum

,

João M. Pereira

CoRR, 2024

2022

Identifying Latent Stochastic Differential Equations.

[BibT_eX]

[DOI]

,

João M. Pereira

,

,

IEEE Trans. Signal Process., 2022

Tensor Moments of Gaussian Mixture Models: Theory and Applications.

[BibT_eX]

[DOI]

João M. Pereira

,

,

Tamara G. Kolda

CoRR, 2022

Modeling extremes with d-max-decreasing neural networks.

[BibT_eX]

[DOI]

,

Khalil Elkhalil

,

,

João M. Pereira

,

,

Jose H. Blanchet

,

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

Deep Extreme Value Copulas for Estimation and Sampling.

[BibT_eX]

[DOI]

,

Khalil Elkhalil

,

João M. Pereira

,

,

Jose H. Blanchet

,

CoRR, 2021

Landscape analysis of an improved power method for tensor decomposition.

[BibT_eX]

[DOI]

,

,

João M. Pereira

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Learning latent stochastic differential equations with variational auto-encoders.

[BibT_eX]

[DOI]

,

João M. Pereira

,

,

CoRR, 2020

Robust Marine Buoy Placement for Ship Detection Using Dropout K-Means.

[BibT_eX]

[DOI]

,

João M. Pereira

,

,

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Learning Partial Differential Equations From Data Using Neural Networks.

[BibT_eX]

[DOI]

,

João M. Pereira

,

Robert J. Ravier

,

,

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019

Multireference Alignment Is Easier With an Aperiodic Translation Distribution.

[BibT_eX]

[DOI]

,

,

William E. Leeb

,

João M. Pereira

,

,

IEEE Trans. Inf. Theory, 2019

Subspace power method for symmetric tensor decomposition and generalized PCA.

[BibT_eX]

[DOI]

,

João M. Pereira

CoRR, 2019

2018

Estimation in the Group Action Channel.

[BibT_eX]

[DOI]

,

João M. Pereira

,

Proceedings of the 2018 IEEE International Symposium on Information Theory, 2018

2017

Sample complexity of the boolean multireference alignment problem.

[BibT_eX]

[DOI]

,

João M. Pereira

,

Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017

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