Papers -- Akyildiz Group

This page contains publications exclusively produced within the group (hence excluding other publications of members).

Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics, J. Marks, T. Y. J. Wang, O. D. Akyildiz. 2025, [arXiv].
Uniform-in-time convergence bounds for Persistent Contrastive Divergence Algorithms, P. F. V. Oliva, O. D. Akyildiz, A. B. Duncan. 2025, [arXiv].
Training Latent Diffusion Models with Interacting Particle Algorithms, T. Y. J. Wang, J. Kuntz, O. D. Akyildiz. 2025, [arXiv].
Non-asymptotic Analysis of Diffusion Annealed Langevin Monte Carlo for Generative Modelling, P. Cordero-Encinar, O. D. Akyildiz, A. B. Duncan. 2025, [arXiv].
Kinetic Interacting Particle Langevin Monte Carlo, P. F. Valsecchi Oliva, O. D. Akyildiz, 2024, [arXiv].

Sampling by averaging: A multiscale approach to score estimation, P. Cordero-Encinar, A. B. Duncan, S. Reich, O. D. Akyildiz. NeurIPS 2025, [arXiv].
Learning Latent Variable Models via Jarzynski-adjusted Langevin Algorithm, J. Cuin, D. Carbone, O. D. Akyildiz. NeurIPS 2025, [arXiv].
On diffusion posterior sampling via sequential Monte Carlo for zero-shot scaffolding of protein motifs, J. M. Young, O. D. Akyildiz. Transactions on Machine Learning Research (TMLR), 2025, [journal], [arXiv].
Nudging state-space models for Bayesian filtering under misspecified dynamics, F. Gonzalez, O. D. Akyildiz, D. Crisan, J. Miguez. Statistics and Computing, 2025, [journal], [arXiv].
Proximal Interacting Particle Langevin Algorithms, P. C. Encinar, F. R. Crucinio, O. D. Akyildiz, Uncertainty in Artificial Intelligence (UAI), Best Student Paper Award, 2025, [proceedings], [arXiv].

A Gradient Flow approach to Solving Inverse Problems with Latent Diffusion Models, Tim Y. J. Wang, O. D. Akyildiz. NeurIPS Workshop Frontiers in Probabilistic Inference: Sampling Meets Learning, 2025, [arXiv].

Adaptively Optimised Adaptive Importance Samplers, C. A. C. C. Perello, Ö. D. Akyildiz, 2023, [arXiv].