A research team has developed a novel direct sampling method based on deep generative models. Their method enables efficient ...

A research team led by Prof. PAN Ding, Associate Professor from the Departments of Physics and Chemistry, and Dr. LI Shuo-Hui ...

Aim: Spatial sampling bias (SSB) is a feature of opportunistically sampled species records. Species distribution models (SDMs) built using these data (i.e. presence-background models) can produce ...

Aim: Accounting for sampling bias is the greatest challenge facing presence-only and presence-background species distribution models; no matter what type of model is chosen, using biased data will ...

No personalisation – generic sampling with no understanding of the target audience leads to low conversion rates. Poor targeting and poor distribution. No follow-up strategy – how are the ...

DPM-Solver++ solves the diffusion ODE with the data prediction model and adopts thresholding methods to keep the solution matches training data distribution.