2 citations · 4 across the 3 of their papers we have counts for
3 papers
Lookahead Diffusion Probabilistic Models for Refining Mean Estimation
Guoqiang Zhang, Niwa Kenta, W. Bastiaan Kleijn
We propose lookahead diffusion probabilistic models (LA-DPMs) to exploit the correlation in the outputs of the deep neural networks (DNNs) over subsequent timesteps in diffusion pr…
On Accelerating Diffusion-Based Sampling Process via Improved Integration Approximation
Guoqiang Zhang, Niwa Kenta, W. Bastiaan Kleijn
A popular approach to sample a diffusion-based generative model is to solve an ordinary differential equation (ODE). In existing samplers, the coefficients of the ODE solvers are p…
Extending AdamW by Leveraging Its Second Moment and Magnitude
Guoqiang Zhang, Niwa Kenta, W. Bastiaan Kleijn
Recent work [4] analyses the local convergence of Adam in a neighbourhood of an optimal solution for a twice-differentiable function. It is found that the learning rate has to be s…