Sub-new stock price prediction, forecasting the price trends of stocks l...
This paper presents a novel network structure with illumination-aware ga...
Self-supervised learning has shown its promising capability in graph
rep...
Large text-to-image diffusion models have impressive capabilities in
gen...
Time-Series Mining (TSM) is an important research area since it shows gr...
This paper proposes a novel module called middle spectrum grouped convol...
In this paper, we propose a novel multi-modal framework for Scene Text V...
We consider the task of generating realistic 3D shapes, which is useful ...
We present a novel camera path optimization framework for the task of on...
We consider the problem of iterative machine teaching, where a teacher
s...
It has been observed that neural networks perform poorly when the data o...
In light of the smoothness property brought by skip connections in ResNe...
High dynamic range (HDR) deghosting algorithms aim to generate ghost-fre...
This paper considers the problem of unsupervised 3D object reconstructio...
Ring signatures enable a user to sign messages on behalf of an arbitrary...
We propose a unifying view to analyze the representation quality of
self...
This paper reviews the challenge on constrained high dynamic range (HDR)...
We present energy-based generative flow networks (EB-GFN), a novel
proba...
One of the main challenges for hierarchical clustering is how to
appropr...
In this paper, we consider the problem of iterative machine teaching, wh...
We present an end-to-end, model-based deep reinforcement learning agent ...
In this paper, we present an attention-guided deformable convolutional
n...
Recent studies in big data analytics and natural language processing dev...
Due to the over-parameterization nature, neural networks are a powerful ...
This paper extends Bayesian mortality projection models for multiple
pop...
An ideal safe workplace is described as a place where staffs fulfill
res...
Breast cancer is the second leading cause of cancer-related death after ...
The improvement of mortality projection is a pivotal topic in the divers...
The inductive bias of a neural network is largely determined by the
arch...
Tie strength prediction, sometimes named weight prediction, is vital in
...
The technology of face recognition has made some progress in recent year...
Searching persons in large-scale image databases with the query of natur...
Inner product-based convolution has been the founding stone of convoluti...
Skull stripping is usually the first step for most brain analysisprocess...
Recent work on minimum hyperspherical energy (MHE) has demonstrated its
...
We present an efficient algorithm for maximum likelihood estimation (MLE...
Neural networks are a powerful class of nonlinear functions that can be
...
Inner product-based convolution has been a central component of convolut...
We consider the problems of learning forward models that map state to
hi...
Low-shot learning methods for image classification support learning from...
With the impressive capability to capture visual content, deep convoluti...
We consider Bayesian analysis of a class of multiple changepoint models....