Author: Simon Benaïchouche

Simon Benaïchouche received his M.Sc. in Mathematics in 2018. He is currently a Ph.D. candidate at the IMT Atlantique (France), where his research focuses on using deep learning techniques for data assimilation problems. His expertise includes inverse problems in geosciences, uncertainty quantification, and learning physical systems from data.

A New AI Approach Based On Operator Splitting Methods For Accelerating Guided Sampling in Diffusion Models

Diffusion models have recently achieved state-of-the-art results in content generation, including images, videos, and music. In this paper, researchers from VISTEC in Thailand focus...

Researchers at the University of Maryland Propose Cold Diffusion: A Diffusion Model with Deterministic Perturbations

Diffusion models can be interpreted as stochastic encoder/decoder architectures, which are built around a residual architecture that successively applies a learned transformation. To this,...

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