In this paper, we propose an energy stable network (EStable-Net) for sol...
Pre-trained large transformer models have achieved remarkable performanc...
Vessel image segmentation plays a pivotal role in medical diagnostics, a...
Overlapped Speech Detection (OSD) is an important part of speech applica...
Understanding the life cycle of the machine learning (ML) model is an
in...
The Merriman-Bence-Osher threshold dynamics method is an efficient algor...
In this paper, we investigate the training process of generative network...
AI-powered programming language generation (PLG) models have gained
incr...
This paper addresses the problem of nearly optimal Vapnik–Chervonenkis
d...
We use the score-based transport modeling method to solve the mean-field...
Despite the fact that DeepFake forgery detection algorithms have achieve...
In this paper, we propose a novel approach to generative modeling using ...
This paper aims to construct a valid and efficient confidence interval f...
Deep neural networks (DNNs) recently emerged as a promising tool for
ana...
To enable the pre-trained models to be fine-tuned with local data on edg...
This paper focuses on leveraging deep representation learning (DRL) for
...
Based on the Denoising Diffusion Probabilistic Model (DDPM), medical ima...
Multi-modal neuroimaging technology has greatlly facilitated the efficie...
We study the stochastic contextual bandit with knapsacks (CBwK) problem,...
Neural-network-based approaches recently emerged in the field of data
co...
The brain age has been proven to be a phenotype of relevance to cognitiv...
Recently, physiological signal-based biometric systems have received wid...
In this paper, we establish a neural network to approximate functionals,...
The ever-growing model size and scale of compute have attracted increasi...
In previous work, we proposed a variational autoencoder-based (VAE) Baye...
Unobservable physiological signals enhance biometric authentication syst...
Automatic Speech Recognition services (ASRs) inherit deep neural network...
Biometric authentication prospered during the 2010s. Vulnerability to
sp...
Recently, variational autoencoder (VAE), a deep representation learning ...
Rowhammer has drawn much attention from both academia and industry in th...
Pre-trained language models have achieved state-of-the-art results in va...
The Android system manages access to sensitive APIs by permission
enforc...
Background: Electronic Health Records (EHRs) contain rich information of...
Pruning is a model compression method that removes redundant parameters ...
Deep Neural Network (DNN), one of the most powerful machine learning
alg...
The proliferation of Internet of Things (IoT) devices has made people's ...
In this paper, we prove the convergence from the atomistic model to the
...
Stealing attack against controlled information, along with the increasin...
Fuzzing is one of the most effective technique to identify potential sof...
The Tangle-based structure becomes one of the most promising solutions w...
Deep learning techniques have shown their success in medical image
segme...
In this paper, we propose a novel supervised single-channel speech
enhan...
Computer users are generally faced with difficulties in making correct
s...
In this paper, we present the design and implementation of a Systematic
...
Deep learning (DL) based predictive models from electronic health record...
Chinese word segmentation is necessary to provide word-level information...
A continuum model of the two dimensional low angle grain boundary motion...
A continuum model of the two dimensional low angle grain boundary motion...
Biomedical data are widely accepted in developing prediction models for
...
Deep Neural Networks (DNNs) are vulnerable to deliberately crafted
adver...