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stat.ML2024
Scalable Implicit Graphon Learning
Ali Azizpour, Nicolas Zilberstein, Santiago Segarra
Graphons are continuous models that represent the structure of graphs and allow the generation of graphs of varying sizes. We propose Scalable Implicit Graphon Learning (SIGL), a s…
stat.ML2023
Solving Linear Inverse Problems using Higher-Order Annealed Langevin Diffusion
Nicolas Zilberstein, Ashutosh Sabharwal, Santiago Segarra
We propose a solution for linear inverse problems based on higher-order Langevin diffusion. More precisely, we propose pre-conditioned second-order and third-order Langevin dynamic…