Diego Mesquita

Since 2022, I am an assistant professor at FGV's EMAp. I am broadly interested in fundamental ML research, with a special focus on probabilistic methods and geometric deep learning.

Follow me on twitter @wkly_infrmtive for somewhat regular updates and for occasional bad jokes. You can also contact me through diego.mesquita@fgv.br

Want to work with me? I'm always looking for excellent post-docs and PhD/MSc students.

Post-doc positions: send me an email with your CV, a brief motivation, and a pointer to your favorite work.
MSc/PhD students: In both cases, you need to sign up for EMAp's selective process. For PhDs, I strongly encourage you to contact me before applying.

I am committed to foster diversity and encourage folks from different backgrounds (e.g., nationality, sex, gender, and religion) to apply.

Selected publications

T. da Silva, D. de Souza, D. Mesquita. Streaming Bayes GFlowNets NeurIPS 2024 [video]
T. da Silva, E. Silva, D. Mesquita. On Divergence Measures for Training GFlowNets NeurIPS 2024 [video]
P. Blomstedt, D. Mesquita, O. Rivasplata, J. Lintusaari, T. Sivula. J. Corander, S. Kaski Meta-analysis of Bayesian analyses Bayesian Analysis 2024 .
A. Matias, C. Mattos, J. Gomes, D. Mesquita. Amortized Variational Deep Kernel Learning . ICML 2024 [video]
T. da Silva, A. Souza, L. Carvalho, S. Kaski, D. Mesquita. Embarrassingly Parallel GFlowNets . ICML 2024 [video]
D. de Souza, A. Nikitin, S. T. John, M. Ross, M. A. Álvarez, M. P. Deisenroth, J. Gomes, D. Mesquita, C. Mattos. Thin and deep Gaussian processes . NeurIPS 2023 [video]
T. Pereira, E. Nascimento, L. Resck, D. Mesquita, A. Souza. Distill n' Explain: explaining graph neural networks using simple surrogates . AISTATS 2023 [video]
A. Souza, D. Mesquita, S. Kaski, V. Garg. Provably expressive temporal graph networks. NeurIPS 2022 [video]
D. de Souza, D. Mesquita, S. Kaski, L. Acerbi. Parallel MCMC without embarrassing failures. AISTATS 2022 [video]
K. El Mekkaoui, D. Mesquita, P. Blomstedt, S. Kaski. Federated stochastic gradient Langevin dynamics. UAI 2021 [video]
D. Mesquita, A. Souza, S. Kaski. Rethinking pooling in graph neural networks.NeurIPS 2020 [video]
D. de Souza, D. Mesquita, J. Gomes, C. Mattos. Learning GPLVM with arbitrary kernels using the unscented transformation. AISTATS 2020 [video]
D. Mesquita, P. Blomstedt, S. Kaski. Parallel MCMC using deep invertible transformations UAI 2019

Preprints

E. Nascimento, D. Mesquita, S. Kaski, A. Souza In-n-Out: Calibrating Graph Neural Networks for Link Prediction .
T. da Silva, A. E. Silva, A. Ribeiro, A. Góis, D. Heider, S. Kaski, D. Mesquita Human-in-the-Loop Causal Discovery under Latent Confounding using Ancestral GFlowNets .

For a full list, have a look at my Google Scholar page.

Supervision

Post-docs

Eliezer Silva

Doctoral students

Tamara Pereira
Tiago da Silva

Master students

Alumni

Jamille Feitosa (Post-doc)
Mariana Neves (Master)
João Duim (Bachelor)
Eduardo Guimarães (Bachelor)
Tuomas Aarnio (Bachelor)
Antti Kumpumäki (Bachelor)