Diego Mesquita

42 papers A* 10A 6B 1Journal 22Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Avoid What You Know: Divergent Trajectory Balance for GFlowNets. CoRR Pedro Dall'Antonia, Tiago da Silva, Daniel Csillag, Salem Lahlou, Diego Mesquita
2025	J	`jnl`	Boosted GFlowNets: Improving Exploration via Sequential Learning. CoRR Pedro Dall'Antonia, Tiago da Silva, Daniel Augusto de Souza, César Lincoln C. Mattos, Diego Mesquita
2025	J	`jnl`	Cooperative Sheaf Neural Networks. CoRR André Ribeiro, Ana Luiza Tenorio, Juan Belieni, Amauri H. Souza, Diego Mesquita
2025	J	`jnl`	Differentially Private E-Values. CoRR Daniel Csillag, Diego Mesquita
2025	A*	`conf`	Differentially Private Selection Using Smooth Sensitivity. SP Iago C. Chaves, Victor A. E. de Farias, Amanda Perez, Diego Mesquita, Javam C. Machado
2025	J	`jnl`	Differentially Private Selection using Smooth Sensitivity. CoRR Iago C. Chaves, Victor A. E. de Farias, Amanda Perez, Diego Mesquita, Javam C. Machado
2025	A*	`conf`	Generalization and Distributed Learning of GFlowNets. ICLR Tiago Silva, Amauri H. Souza, Omar Rivasplata, Vikas Garg, Samuel Kaski, Diego Mesquita
2025	J	`jnl`	Infinite Neural Operators: Gaussian processes on functions. CoRR Daniel Augusto de Souza, Yuchen Zhu, Harry Jake Cunningham, Yuri F. Saporito, Diego Mesquita, Marc Peter Deisenroth
2025	J	`jnl`	On the Identifiability of Tensor Ranks via Prior Predictive Matching. CoRR Eliezer de Souza da Silva, Arto Klami, Diego Mesquita, Iñigo Urteaga
2025	A*	`conf`	When do GFlowNets learn the right distribution? ICLR Tiago da Silva, Rodrigo Barreto Alves, Eliezer de Souza da Silva, Amauri H. Souza, Vikas Garg, Samuel Kaski, Diego Mesquita
2024	—	`conf`	A Contrastive Objective for Training Continuous Generative Flow Networks. BRACIS (1) Tiago da Silva, Diego Mesquita
2024	A*	`conf`	Amortized Variational Deep Kernel Learning. ICML Alan L. S. Matias, César Lincoln C. Mattos, João Paulo Pordeus Gomes, Diego Mesquita
2024	J	`jnl`	Bayesian ART for incomplete datasets. Appl. Soft Comput. Alan L. S. Matias, João Paulo Pordeus Gomes, César Lincoln C. Mattos, Ajalmar R. da Rocha Neto, Diego Mesquita
2024	A*	`conf`	Embarrassingly Parallel GFlowNets. ICML Tiago da Silva, Luiz Max Carvalho, Amauri H. Souza, Samuel Kaski, Diego Mesquita
2024	J	`jnl`	Embarrassingly Parallel GFlowNets. CoRR Tiago da Silva, Luiz Max Carvalho, Amauri H. Souza, Samuel Kaski, Diego Mesquita
2024	J	`jnl`	In-n-Out: Calibrating Graph Neural Networks for Link Prediction. CoRR Erik Nascimento, Diego Mesquita, Samuel Kaski, Amauri H. Souza
2024	A*	`conf`	On Divergence Measures for Training GFlowNets. NeurIPS Tiago da Silva, Eliezer de Souza da Silva, Diego Mesquita
2024	J	`jnl`	On Divergence Measures for Training GFlowNets. CoRR Tiago da Silva, Eliezer de Souza da Silva, Diego Mesquita
2024	A*	`conf`	Streaming Bayes GFlowNets. NeurIPS Tiago da Silva, Daniel Augusto de Souza, Diego Mesquita
2024	J	`jnl`	Streaming Bayes GFlowNets. CoRR Tiago da Silva, Daniel Augusto de Souza, Diego Mesquita
2023	A	`conf`	Distill n' Explain: explaining graph neural networks using simple surrogates. AISTATS Tamara A. Pereira, Erik Nascimento, Lucas E. Resck, Diego Mesquita, Amauri H. Souza
2023	J	`jnl`	Distill n' Explain: explaining graph neural networks using simple surrogates. CoRR Tamara A. Pereira, Erik Nascimento, Lucas E. Resck, Diego Mesquita, Amauri H. Souza
2023	J	`jnl`	Human-in-the-Loop Causal Discovery under Latent Confounding using Ancestral GFlowNets. CoRR Tiago da Silva, Eliezer S. Silva, Adèle H. Ribeiro, António Góis, Dominik Heider, Samuel Kaski, Diego Mesquita
2023	J	`jnl`	Locking and Quacking: Stacking Bayesian model predictions by log-pooling and superposition. CoRR Yuling Yao, Luiz Max Carvalho, Diego Mesquita, Yann McLatchie
2023	J	`jnl`	Thin and Deep Gaussian Processes. CoRR 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
2023	A*	`conf`	Thin and deep Gaussian processes. NeurIPS 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
2022	A	`conf`	Bayesian Analysis of Bug-Fixing Time using Report Data. ESEM Renan Gomes Vieira, Diego Mesquita, César Lincoln C. Mattos, Ricardo Britto, Lincoln S. Rocha, João Gomes
2022	J	`jnl`	Bayesian Multilateration. IEEE Signal Process. Lett. Alisson S. C. Alencar, César L. C. Mattos, João P. P. Gomes, Diego Mesquita
2022	—	`conf`	ConveXplainer for Graph Neural Networks. BRACIS (2) Tamara A. Pereira, Erik Jhones F. do Nascimento, Diego Mesquita, Amauri H. Souza
2022	A	`conf`	Parallel MCMC Without Embarrassing Failures. AISTATS Daniel Augusto de Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi
2022	J	`jnl`	Parallel MCMC Without Embarrassing Failures. CoRR Daniel Augusto de Souza, Diego Mesquita, Samuel Kaski, Luigi Acerbi
2022	A*	`conf`	Provably expressive temporal graph networks. NeurIPS Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg
2022	J	`jnl`	Provably expressive temporal graph networks. CoRR Amauri H. Souza, Diego Mesquita, Samuel Kaski, Vikas Garg
2021	—	`—`	Advances in distributed Bayesian inference and graph neural networks. Diego Mesquita
2021	A	`conf`	Federated stochastic gradient Langevin dynamics. UAI Khaoula el Mekkaoui, Diego Mesquita, Paul Blomstedt, Samuel Kaski
2021	B	`conf`	Improving Graph Variational Autoencoders with Multi-Hop Simple Convolutions. ESANN Erik Jhones F. do Nascimento, Amauri H. Souza, Diego Mesquita
2021	A	`conf`	Learning GPLVM with arbitrary kernels using the unscented transformation. AISTATS Daniel Augusto de Souza, Diego Mesquita, João Paulo Pordeus Gomes, César Lincoln C. Mattos
2020	A*	`conf`	Rethinking pooling in graph neural networks. NeurIPS Diego Mesquita, Amauri H. Souza Jr., Samuel Kaski
2020	J	`jnl`	Rethinking pooling in graph neural networks. CoRR Diego Mesquita, Amauri H. Souza Jr., Samuel Kaski
2020	J	`jnl`	Variance reduction for distributed stochastic gradient MCMC. CoRR Khaoula el Mekkaoui, Diego Mesquita, Paul Blomstedt, Samuel Kaski
2019	A	`conf`	Embarrassingly Parallel MCMC using Deep Invertible Transformations. UAI Diego Mesquita, Paul Blomstedt, Samuel Kaski
2019	J	`jnl`	Embarrassingly parallel MCMC using deep invertible transformations. CoRR Diego Mesquita, Paul Blomstedt, Samuel Kaski