Mounting evidence underscores the prevalent hierarchical organization of...
In the era of big data, the issue of data quality has become increasingl...
Entanglement propagation provides a key routine to understand quantum
ma...
The extraordinary ability of generative models to generate photographic
...
Real-world programs expecting structured inputs often has a format-parsi...
We consider random walks on discrete state spaces, such as general undir...
Wireless sensors are everywhere. To address their energy supply, we prop...
In this paper, we propose YOSO, a real-time panoptic segmentation framew...
Combination therapy with multiple drugs is a potent therapy strategy for...
Deep neural networks have been proven effective in a wide range of tasks...
The magnitude of Pearson correlation between two scalar random variables...
Real-world image super-resolution (RISR) has received increased focus fo...
The application of superconducting materials is becoming more and more
w...
We study the file transfer problem in opportunistic spectrum access (OSA...
Over past few years afterward the birth of ResNet, skip connection has b...
We consider the stochastic gradient descent (SGD) algorithm driven by a
...
Applying artificial intelligence to scientific problems (namely AI for
s...
Time-series forecasting plays an important role in many real-world scena...
As deep learning becomes the mainstream in the field of natural language...
Accurate traffic forecasting, the foundation of intelligent transportati...
Recent work has shown that Binarized Neural Networks (BNNs) are able to
...
Patent data have long been used for engineering design research because ...
The Opportunistic Spectrum Access (OSA) model has been developed for the...
Density functional theory and its optimization algorithm are the main me...
While recent deep deblurring algorithms have achieved remarkable progres...
Correlated data are ubiquitous in today's data-driven society. A fundame...
Multi-view representation learning captures comprehensive information fr...
The nonlocal-based blocks are designed for capturing long-range
spatial-...
In large technology companies, the requirements for managing and organiz...
The hybridizations of machine learning and quantum physics have caused
e...
Design-by-Analogy (DbA) is a design methodology wherein new solutions,
o...
Learning node representation that incorporating information from graph
s...
End-to-end paradigms significantly improve the accuracy of various
deep-...
Superpixel is generated by automatically clustering pixels in an image i...
Recently, image-to-image translation has made significant progress in
ac...
In this paper, we focus on the performance of vehicle-to-vehicle (V2V)
c...
Machine Reading Comprehension (MRC) is a challenging NLP research field ...
Full-spectrum ranging from sub 6 GHz to THz and visible light will be
ex...
Recently, the motion averaging method has been introduced as an effectiv...
Deep Neural Networks (DNNs) are central to deep learning, and understand...
The patent database is often used in searches of inspirational stimuli f...
With the wireless communication being more various in the future, it's
b...
Background: Elderly patients with MODS have high risk of death and poor
...
Learning representations with diversified information remains an open
pr...
Unpaired Image-to-Image Translation (UIT) focuses on translating images ...
This paper focuses on robotic picking tasks in cluttered scenario. Becau...
This paper focuses on a robotic picking tasks in cluttered scenario. Bec...
Most existing visual search systems are deployed based upon fixed kinds ...
While the use of bottom-up local operators in convolutional neural netwo...
Cell division timing is critical for cell fate specification and
morphog...