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Rembert Daems

3 accepted papers

2025

Fractional Diffusion Bridge Models

NeurIPS 2025poster

We present *Fractional Diffusion Bridge Models* (FDBM), a novel generative diffusion bridge framework driven by the rich and non-Markovian fractional Brownian motion (fBM). Real stochastic processes exhibit a degree of memory effects (correlations in time), long-range dependencies, roughness and ano…

Cited by 0SourceScholar
2024

Generative Fractional Diffusion Models

NeurIPS 2024poster

We introduce the first continuous-time score-based generative model that leverages fractional diffusion processes for its underlying dynamics. Although diffusion models have excelled at capturing data distributions, they still suffer from various limitations such as slow convergence, mode-collapse o…

2024

Variational Inference for SDEs Driven by Fractional Noise

ICLR 2024spotlight

We present a novel variational framework for performing inference in (neural) stochastic differential equations (SDEs) driven by Markov-approximate fractional Brownian motion (fBM). SDEs offer a versatile tool for modeling real-world continuous-time dynamic systems with inherent noise and randomness…

Cited by 6SourcePDFScholar