Daniel Augusto R. M. A. de Souza

According to our database, Daniel Augusto R. M. A. de Souza authored at least 11 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Boosted GFlowNets: Improving Exploration via Sequential Learning.

Pedro Dall'Antonia, Tiago da Silva, Daniel Augusto de Souza, César Lincoln C. Mattos, Diego Mesquita

CoRR, November, 2025

Infinite Neural Operators: Gaussian processes on functions.

Daniel Augusto de Souza, Yuchen Zhu, Jake Cunningham, Yuri F. Saporito, Diego Mesquita, Marc Peter Deisenroth

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

When Can Proxies Improve the Sample Complexity of Preference Learning?

Yuchen Zhu, Daniel Augusto de Souza, Zhengyan Shi, Mengyue Yang, Pasquale Minervini, Matt J. Kusner, Alexander Nicholas D'Amour

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Streaming Bayes GFlowNets.

Tiago da Silva, Daniel Augusto de Souza, Diego Mesquita

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Actually Sparse Variational Gaussian Processes.

Harry Jake Cunningham, Daniel Augusto de Souza, So Takao, Mark van der Wilk, Marc Peter Deisenroth

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

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

Parallel MCMC Without Embarrassing Failures.

Daniel Augusto de Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Learning GPLVM with arbitrary kernels using the unscented transformation.

Daniel Augusto de Souza, Diego Mesquita, João Paulo Pordeus Gomes, César Lincoln C. Mattos

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

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

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

Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019