A model of stochastic memoization and name generation in probabilistic programming: categorical semantics via monads on presheaf categories. - Younesse Kaddar; Sam Staton (MFPS, 2023)

Affine Monads and Lazy Structures for Bayesian Programming. - Swaraj Dash; Younesse Kaddar; Hugo Paquet; Sam Staton (Proc. ACM Program. Lang., 2023)

Amortizing intractable inference in large language models. - Edward J. Hu; Moksh Jain; Eric Elmoznino; Younesse Kaddar; Guillaume Lajoie; Yoshua Bengio; Nikolay Malkin (ICLR, 2024)

Probabilistic Programming Interfaces for Random Graphs: Markov Categories, Graphons, and Nominal Sets. - Nathanael L. Ackerman; Cameron E. Freer; Younesse Kaddar; Jacek Karwowski; Sean K. Moss; Daniel M. Roy 001; Sam Staton; Hongseok Yang (Proc. ACM Program. Lang., 2024)

Can a Bayesian Oracle Prevent Harm from an Agent? - Yoshua Bengio; Michael K. Cohen; Nikolay Malkin; Matt MacDermott; Damiano Fornasiere; Pietro Greiner; Younesse Kaddar (UAI, 2025)

Uncertainty-Aware Step-wise Verification with Generative Reward Models. - Zihuiwen Ye; Luckeciano Carvalho Melo; Younesse Kaddar; Phil Blunsom; Sam Staton; Yarin Gal (CoRR, 2025)