Diego Mesquita

15 papers · 2019–2026 · 5 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (30) 🏃 Academic Marathon · Sprint 🐣 Hot Topic Early Bird

🚀 Conference Pioneer 🔥 Unstoppable · Bronze ❓ The Questioner 💎 Century Club · Bronze 🗃️ Keyword Collector (75)

Venues

NeurIPS (5) AISTATS (3) UAI (3) ICLR (2) ICML (2)

Top co-authors

Samuel Kaski (8) César Lincoln Mattos (3) Vikas Garg (3) Tiago da Silva (3) Amauri Souza (3) Amauri H Souza (3) Tiago Silva (3) João Paulo Gomes (2) Paul Blomstedt (2) Daniel Augusto de Souza (2)

Research topics

Machine Learning (14) Deep Learning (10) Optimization & Theory (8) Artificial Intelligence (7) Models (7) Architectures (4) Bayesian & Probabilistic · Artificial Intelligence (4) Bayesian & Probabilistic · Machine Learning (4) Core Methods (4) Mathematics & Optimization (2) Core AI (2) Learning Types (2) Optimization (2) Reinforcement Learning (1) Application Areas (1)

Keywords

generative flow network (5) bayesian inference (4) graph neural network (4) variational inference (3) markov chain monte carlo (3) parallel computing (2) surrogate model (2) metric learning (1) langevin dynamics (1) active learning (1) knowledge distillation (1) distributed learning (1) posterior sampling (1) kernel learning (1) uncertainty quantification (1) stochastic gradient (1) gaussian process (1) sampling distribution (1) gradient estimation (1) divergence minimization (1)

Papers

Particle GFlowNets: Rethinking Generative Marginalization Models UAI 2026 Generalization and Distributed Learning of GFlowNets ICLR 2025 When do GFlowNets learn the right distribution? ICLR 2025 Amortized Variational Deep Kernel Learning ICML 2024 Embarrassingly Parallel GFlowNets ICML 2024 On Divergence Measures for Training GFlowNets NeurIPS 2024 Streaming Bayes GFlowNets NeurIPS 2024 Distill n’ Explain: explaining graph neural networks using simple surrogates AISTATS 2023 Thin and deep Gaussian processes NeurIPS 2023 Parallel MCMC Without Embarrassing Failures AISTATS 2022 Provably expressive temporal graph networks NeurIPS 2022 Federated stochastic gradient Langevin dynamics UAI 2021 Learning GPLVM with arbitrary kernels using the unscented transformation AISTATS 2021 Rethinking pooling in graph neural networks NeurIPS 2020 Embarrassingly Parallel MCMC using Deep Invertible Transformations UAI 2019