Journal of chemical information and modeling
Oct 27, 2022
Molecular representation is a critical part of various prediction tasks for physicochemical properties of molecules and drug design. As graph notations are common in expressing the structural information of chemical compounds, graph neural networks (...
The journal of physical chemistry. A
Oct 27, 2022
Neural network potentials are emerging as promising classical force fields that can enable long-time and large-length scale simulations at close to accuracies. They learn the underlying potential energy surface by mapping the Cartesian coordinates o...
IEEE transactions on medical imaging
Oct 27, 2022
Medical image segmentation is fundamental and essential for the analysis of medical images. Although prevalent success has been achieved by convolutional neural networks (CNN), challenges are encountered in the domain of medical image analysis by two...
IEEE transactions on medical imaging
Oct 27, 2022
Domain adaptation techniques have been demonstrated to be effective in addressing label deficiency challenges in medical image segmentation. However, conventional domain adaptation based approaches often concentrate on matching global marginal distri...
IEEE transactions on medical imaging
Oct 27, 2022
Recent advances in deep learning led to several algorithms for the accurate diagnosis of pneumonia from chest X-rays. However, these models require large training medical datasets, which are sparse, isolated, and generally private. Furthermore, these...
IEEE transactions on medical imaging
Oct 27, 2022
Automatic surgical scene segmentation is fundamental for facilitating cognitive intelligence in the modern operating theatre. Previous works rely on conventional aggregation modules (e.g., dilated convolution, convolutional LSTM), which only make use...
IEEE transactions on neural networks and learning systems
Oct 27, 2022
Tracking-by-detection is a very popular framework for single-object tracking that attempts to search the target object within a local search window for each frame. Although such a local search mechanism works well on simple videos, however, it makes ...
IEEE transactions on neural networks and learning systems
Oct 27, 2022
As an important and challenging problem, multidomain learning (MDL) typically seeks a set of effective lightweight domain-specific adapter modules plugged into a common domain-agnostic network. Usually, existing ways of adapter plugging and structure...
IEEE transactions on neural networks and learning systems
Oct 27, 2022
Auxiliary rewards are widely used in complex reinforcement learning tasks. However, previous work can hardly avoid the interference of auxiliary rewards on pursuing the main rewards, which leads to the destruction of the optimal policy. Thus, it is c...
IEEE transactions on neural networks and learning systems
Oct 27, 2022
It is very challenging for machine learning methods to reach the goal of general-purpose learning since there are so many complicated situations in different tasks. The learning methods need to generate flexible internal representations for all scena...