In contrast to conventional closed-set recognition, open-set recognition...
Given the huge volume of cross-border flows, effective and efficient con...
Understanding the spatio-temporal patterns of the coronavirus disease 20...
Predicting the pose of an object is a core computer vision task. Most de...
Periocular biometric, or peripheral area of ocular, is a collaborative
a...
Nonstationary non-Gaussian spatial data are common in many disciplines,
...
Inference for doubly intractable distributions is challenging because th...
Longitudinal network models are widely used to study the time-varying
re...
In unsupervised novelty detection, a model is trained solely on the in-c...
Doubly intractable distributions commonly arise in many complex statisti...
Monte Carlo maximum likelihood (MCML) provides an elegant approach to fi...
Deep neural networks are widely used and exhibit excellent performance i...
Stacking-based deep neural network (S-DNN) is aggregated with pluralitie...
Doubly intractable distributions arise in many settings, for example in
...