Full Professor, The University of Queensland
2 papers at NeurIPS 2025
Scalable, post-hoc, Bayesian uncertainty quantification method using an ensemble of linearised networks.
We propose LFlow, a training-free framework for solving linear inverse problems using pretrained latent flow priors with theoretically grounded posterior guidance, achieving superior reconstruction quality over latent diffusion baselines.
