| 2025 | ACSSC | Sampling with Shielded Langevin Monte Carlo Using Navigation Potentials. | Nicolas Zilberstein, Santiago Segarra, Luiz Chamon |
| 2025 | AISTATS | Scalable Implicit Graphon Learning. | Ali Azizpour, Nicolas Zilberstein, Santiago Segarra |
| 2025 | ICLR | Repulsive Latent Score Distillation for Solving Inverse Problems. | Nicolas Zilberstein, Morteza Mardani, Santiago Segarra |
| 2024 | ICASSP | End-to-End Learning of Gaussian Mixture Proposals Using Differentiable Particle Filters and Neural Networks. | Benjamin Cox, Sara Prez-Vieites, Nicolas Zilberstein, Martin Sevilla, Santiago Segarra, Vctor Elvira |
| 2024 | ICASSP | Joint Channel Estimation and Data Detection in Massive Mimo Systems Based on Diffusion Models. | Nicolas Zilberstein, Ananthram Swami, Santiago Segarra |
| 2023 | ACSSC | State and Dynamics Estimation with the Kalman-Langevin filter. | Martin Sevilla, Nicolas Zilberstein, Benjamin Cox, Sara Prez-Vieites, Vctor Elvira, Santiago Segarra |
| 2023 | ICASSP | Accelerated Massive MIMO Detector Based on Annealed Underdamped Langevin Dynamics. | Nicolas Zilberstein, Chris Dick, Rahman Doost-Mohammady, Ashutosh Sabharwal, Santiago Segarra |
| 2022 | ICASSP | Unrolling Particles: Unsupervised Learning of Sampling Distributions. | Fernando Gama, Nicolas Zilberstein, Richard G. Baraniuk, Santiago Segarra |