With the rapid development of IT operations, it has become increasingly
...
Learning implicit representations has been a widely used solution for su...
Lossless floating-point time series compression is crucial for a wide ra...
People with Parkinson's Disease experience gait impairments that
signifi...
There are a prohibitively large number of floating-point time series dat...
Aspect-based-sentiment-analysis (ABSA) is a fine-grained sentiment evalu...
Federated learning (FL) is vulnerable to poisoning attacks, where advers...
Time series event detection methods are evaluated mainly by standard
cla...
Deep neural networks are vulnerable to backdoor attacks, where an advers...
It is vital to infer signed distance functions (SDFs) from 3D point clou...
Dynamic graphs arise in various real-world applications, and it is often...
We present a differentiable approach to learn the probabilistic factors ...
Visual odometry is important for plenty of applications such as autonomo...
Inductive one-bit matrix completion is motivated by modern applications ...
In the past decades, lots of progress have been done in the video compre...
Gradient-based explanation is the cornerstone of explainable deep networ...
LiDAR mapping is important yet challenging in self-driving and mobile
ro...
Image super-resolution (SR) serves as a fundamental tool for the process...
Due to the increasing computational demand of Deep Neural Networks (DNNs...
Modeling sparse and dense image matching within a unified functional
cor...
Semi-supervised Anomaly Detection (AD) is a kind of data mining task whi...
Visual place recognition (VPR) using deep networks has achieved
state-of...
We are interested in solving linear systems arising from three applicati...
Trojan attacks pose a severe threat to AI systems. Recent works on
Trans...
Deep-learning-based clinical decision support using structured electroni...
Orchard automation has attracted the attention of researchers recently d...
Deep implicit functions have shown remarkable shape modeling ability in
...
Bird's eye view (BEV) representation is a new perception formulation for...
Recently, physiological signal-based biometric systems have received wid...
Topological loss based on persistent homology has shown promise in vario...
Accurate segmentation of various fine-scale structures from biomedical i...
We introduce an open-source and unified framework for transition analysi...
Trojan attacks raise serious security concerns. In this paper, we invest...
Accurate depth-sensing plays a crucial role in securing a high success r...
Pixel synthesis is a promising research paradigm for image generation, w...
Capturing the dynamics in user preference is crucial to better predict u...
In this paper, we propose a simple yet universal network termed SeqTR fo...
User interests are usually dynamic in the real world, which poses both
t...
The partial differential equation (PDE) plays a significantly important ...
The adversarial risk of a machine learning model has been widely studied...
Persistent homology is perhaps the most popular and useful tool offered ...
Unobservable physiological signals enhance biometric authentication syst...
Automatic Speech Recognition services (ASRs) inherit deep neural network...
Structural accuracy of segmentation is important for finescale structure...
Persistent homology is a widely used theory in topological data analysis...
Biometric authentication prospered during the 2010s. Vulnerability to
sp...
Scene Graph Generation (SGG) aims to build a structured representation o...
Compared to traditional rigid robotics, soft robotics has attracted
incr...
Field robotic harvesting is a promising technique in recent development ...
Most of the existing methods for debaising in click-through rate (CTR)
p...