6 citations · 11 across the 4 of their papers we have counts for
4 papers
DiscDiff: Latent Diffusion Model for DNA Sequence Generation
Zehui Li, Yuhao Ni, William A V Beardall +4
This paper introduces a novel framework for DNA sequence generation, comprising two key components: DiscDiff, a Latent Diffusion Model (LDM) tailored for generating discrete DNA se…
Score Normalization for a Faster Diffusion Exponential Integrator Sampler
Guoxuan Xia, Duolikun Danier, Ayan Das +4
Recently, Zhang et al. have proposed the Diffusion Exponential Integrator Sampler (DEIS) for fast generation of samples from Diffusion Models. It leverages the semi-linear nature o…
Logit-Based Ensemble Distribution Distillation for Robust Autoregressive Sequence Uncertainties
Yassir Fathullah, Guoxuan Xia, Mark Gales
Efficiently and reliably estimating uncertainty is an important objective in deep learning. It is especially pertinent to autoregressive sequence tasks, where training and inferenc…
On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution Detection
Guoxuan Xia, Christos-Savvas Bouganis
The ability to detect Out-of-Distribution (OOD) data is important in safety-critical applications of deep learning. The aim is to separate In-Distribution (ID) data drawn from the…