Model Selection for Bayesian Autoencoders. - Ba-Hien Tran; Simone Rossi 001; Dimitrios Milios; Pietro Michiardi; Edwin V. Bonilla; Maurizio Filippone (NeurIPS, 2021)

All You Need is a Good Functional Prior for Bayesian Deep Learning. - Ba-Hien Tran; Simone Rossi 001; Dimitrios Milios; Maurizio Filippone (J. Mach. Learn. Res., 2022)

Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes. - Ba-Hien Tran; Babak Shahbaba; Stephan Mandt; Maurizio Filippone (ICML, 2023)

One-Line-of-Code Data Mollification Improves Optimization of Likelihood-based Generative Models. - Ba-Hien Tran; Giulio Franzese; Pietro Michiardi; Maurizio Filippone (NeurIPS, 2023)

Spatial Bayesian Neural Networks. - Andrew Zammit-Mangion; Michael D. Kaminski; Ba-Hien Tran; Maurizio Filippone; Noel Cressie (CoRR, 2023)

Advancing Bayesian Deep Learning: Sensible Priors and Accelerated Inference. (Faire progresser l'apprentissage profond bayésien: priors sensibles et inférence accélérée). - Ba-Hien Tran (2023)

BOLD: Boolean Logic Deep Learning. - Van Minh Nguyen; Cristian Ocampo-Blandon; Aymen Askri; Louis Leconte; Ba-Hien Tran (NeurIPS, 2024)

Robust Classification by Coupling Data Mollification with Label Smoothing. - Markus Heinonen; Ba-Hien Tran; Michael Kampffmeyer; Maurizio Filippone (AISTATS, 2025)

Optimizing Data Augmentation through Bayesian Model Selection. - Madi Matymov; Ba-Hien Tran; Michael Kampffmeyer; Markus Heinonen; Maurizio Filippone (CoRR, 2025)

Highly Efficient and Effective LLMs with Multi-Boolean Architectures. - Ba-Hien Tran; Van Minh Nguyen (CoRR, 2025)