Diego Mesquita
14 papers · 2019–2025 · 5 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π Interdisciplinary Bridge π§ Keyword Pioneer πΊοΈ Taxonomy Completionist (10) π Conference Polyglot (5)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
ποΈ
Keyword Collector
(51)
π
Conference Pioneer
π
Century Club
(14)
π₯
Unstoppable
(7)
β
The Questioner
Conferences
NIPS (5)
AISTATS (3)
ICLR (2)
ICML (2)
UAI (2)
Top co-authors
Keywords
bayesian inference
(4)
graph neural network
(3)
variational inference
(3)
parallel computing
(2)
surrogate model
(2)
markov chain monte carlo
(2)
generative flow network
(2)
metric learning
(1)
langevin dynamics
(1)
active learning
(1)
knowledge distillation
(1)
posterior sampling
(1)
kernel learning
(1)
gradient estimation
(1)
uncertainty quantification
(1)
message passing
(1)
stochastic gradient
(1)
importance sampling
(1)
gaussian process
(1)
divergence minimization
(1)
Papers
When do GFlowNets learn the right distribution?
ICLR 2025
Generalization and Distributed Learning of GFlowNets
ICLR 2025
Streaming Bayes GFlowNets
NIPS 2024
On Divergence Measures for Training GFlowNets
NIPS 2024
Amortized Variational Deep Kernel Learning
ICML 2024
Embarrassingly Parallel GFlowNets
ICML 2024
Distill nβ Explain: explaining graph neural networks using simple surrogates
AISTATS 2023
Thin and deep Gaussian processes
NIPS 2023
Parallel MCMC Without Embarrassing Failures
AISTATS 2022
Provably expressive temporal graph networks
NIPS 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
NIPS 2020
Embarrassingly Parallel MCMC using Deep Invertible Transformations
UAI 2019