Mesquita, Diego

20 publications

ICLR 2025 Generalization and Distributed Learning of GFlowNets Tiago Silva, Amauri H Souza, Omar Rivasplata, Vikas Garg, Samuel Kaski, Diego Mesquita

NeurIPS 2025 Infinite Neural Operators: Gaussian Processes on Functions Daniel Augusto de Souza, Yuchen Zhu, Harry Jake Cunningham, Yuri Saporito, Diego Mesquita, Marc Peter Deisenroth

ICLR 2025 When Do GFlowNets Learn the Right Distribution? Tiago Silva, Rodrigo Barreto Alves, Eliezer de Souza da Silva, Amauri H Souza, Vikas Garg, Samuel Kaski, Diego Mesquita

ICML 2024 Amortized Variational Deep Kernel Learning Alan L. S. Matias, César Lincoln Mattos, João Paulo Pordeus Gomes, Diego Mesquita

ICMLW 2024 Analyzing GFlowNets: Stability, Expressiveness, and Assessment Tiago Silva, Eliezer de Souza da Silva, Rodrigo Barreto Alves, Luiz Max Carvalho, Amauri H Souza, Samuel Kaski, Vikas Garg, Diego Mesquita

ICML 2024 Embarrassingly Parallel GFlowNets Tiago Silva, Luiz Max Carvalho, Amauri H Souza, Samuel Kaski, Diego Mesquita

NeurIPSW 2024 Human-Aided Discovery of Ancestral Graphs Tiago Silva, Eliezer de Souza da Silva, António Góis, Dominik Heider, Samuel Kaski, Diego Mesquita, Adele H Ribeiro

NeurIPS 2024 On Divergence Measures for Training GFlowNets Tiago da Silva, Eliezer de Souza da Silva, Diego Mesquita

NeurIPSW 2024 On Divergence Measures for Training GFlowNets Tiago Silva, Eliezer de Souza da Silva, Diego Mesquita

NeurIPS 2024 Streaming Bayes GFlowNets Tiago da Silva, Daniel Augusto de Souza, Diego Mesquita

AISTATS 2023 Distill N’ Explain: Explaining Graph Neural Networks Using Simple Surrogates Tamara Pereira, Erik Nascimento, Lucas E. Resck, Diego Mesquita, Amauri Souza

NeurIPS 2023 Thin and Deep Gaussian Processes Daniel Augusto de Souza, Alexander Nikitin, St John, Magnus Ross, Mauricio A Álvarez, Marc Deisenroth, João Paulo Gomes, Diego Mesquita, César Lincoln Mattos

AISTATS 2022 Parallel MCMC Without Embarrassing Failures Daniel A. De Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi

NeurIPSW 2022 Locking and Quacking: Stacking Bayesian Models Predictions by Log-Pooling and Superposition Yuling Yao, Luiz Max Carvalho, Diego Mesquita

NeurIPS 2022 Provably Expressive Temporal Graph Networks Amauri Souza, Diego Mesquita, Samuel Kaski, Vikas Garg

NeurIPSW 2022 Provably Expressive Temporal Graph Networks Amauri H Souza, Diego Mesquita, Samuel Kaski, Vikas Garg

AISTATS 2021 Learning GPLVM with Arbitrary Kernels Using the Unscented Transformation Daniel Souza, Diego Mesquita, João Paulo Gomes, César Lincoln Mattos

UAI 2021 Federated Stochastic Gradient Langevin Dynamics Khaoula Mekkaoui, Diego Mesquita, Paul Blomstedt, Samuel Kaski

NeurIPS 2020 Rethinking Pooling in Graph Neural Networks Diego Mesquita, Amauri Souza, Samuel Kaski

UAI 2019 Embarrassingly Parallel MCMC Using Deep Invertible Transformations Diego Mesquita, Paul Blomstedt, Samuel Kaski