One popular diffusion-based sampling strategy attempts to solve the reve...
We propose lookahead diffusion probabilistic models (LA-DPMs) to exploit...
A number of recent adaptive optimizers improve the generalisation perfor...
Adam and AdaBelief compute and make use of elementwise adaptive stepsize...
Recent work [4] analyses the local convergence of Adam in a neighbourhoo...
This paper presents a novel optimization for differentiable programming ...
The primal-dual method of multipliers (PDMM) was originally designed for...
This paper proposes a dual-supervised uncertainty inference (DS-UI) fram...
Due to lack of data, overfitting ubiquitously exists in real-world
appli...
Channel attention mechanisms, as the key components of some modern
convo...
Generalisation of a deep neural network (DNN) is one major concern when
...
Adaptive gradient methods such as Adam have been shown to be very effect...
This paper considers object detection and 3D estimation using an FMCW ra...
A Bayesian approach termed BAyesian Least Squares Optimization with
Nonn...