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09/06/2023
Enhancing Event Sequence Modeling with Contrastive Relational Inference
Neural temporal point processes(TPPs) have shown promise for modeling co...
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08/26/2023
SamDSK: Combining Segment Anything Model with Domain-Specific Knowledge for Semi-Supervised Learning in Medical Image Segmentation
The Segment Anything Model (SAM) exhibits a capability to segment a wide...
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05/24/2023
Collaborative Recommendation Model Based on Multi-modal Multi-view Attention Network: Movie and literature cases
The existing collaborative recommendation models that use multi-modal in...
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04/22/2023
Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model
The Segment Anything Model (SAM) is a recently developed large model for...
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04/09/2023
AI-assisted Automated Workflow for Real-time X-ray Ptychography Data Analysis via Federated Resources
We present an end-to-end automated workflow that uses large-scale remote...
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02/07/2023
IB-UQ: Information bottleneck based uncertainty quantification for neural function regression and neural operator learning
In this paper, a novel framework is established for uncertainty quantifi...
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02/03/2023
Failure-informed adaptive sampling for PINNs, Part II: combining with re-sampling and subset simulation
This is the second part of our series works on failure-informed adaptive...
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01/13/2023
Prompting Neural Machine Translation with Translation Memories
Improving machine translation (MT) systems with translation memories (TM...
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12/01/2022
A Structure-guided Effective and Temporal-lag Connectivity Network for Revealing Brain Disorder Mechanisms
Brain network provides important insights for the diagnosis of many brai...
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11/24/2022
Identifying discreditable firms in a large-scale ownership network
Violations of laws and regulations about food safety, production safety,...
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11/01/2022
SOLAR: A Highly Optimized Data Loading Framework for Distributed Training of CNN-based Scientific Surrogates
CNN-based surrogates have become prevalent in scientific applications to...
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10/01/2022
Failure-informed adaptive sampling for PINNs
Physics-informed neural networks (PINNs) have emerged as an effective te...
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09/28/2022
Prompt-driven efficient Open-set Semi-supervised Learning
Open-set semi-supervised learning (OSSL) has attracted growing interest,...
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09/26/2022
Myopia prediction for adolescents via time-aware deep learning
Background: Quantitative prediction of the adolescents' spherical equiva...
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09/20/2022
Deep learning at the edge enables real-time streaming ptychographic imaging
Coherent microscopy techniques provide an unparalleled multi-scale view ...
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08/21/2022
A predictor-corrector deep learning algorithm for high dimensional stochastic partial differential equations
In this paper, we present a deep learning-based numerical method for app...
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08/04/2022
Equivalence between Time Series Predictability and Bayes Error Rate
Predictability is an emerging metric that quantifies the highest possibl...
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07/27/2022
Camouflaged Object Detection via Context-aware Cross-level Fusion
Camouflaged object detection (COD) aims to identify the objects that con...
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04/27/2022
Discrete energy analysis of the third-order variable-step BDF time-stepping for diffusion equations
This is one of our series works on discrete energy analysis of the varia...
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03/21/2022
Multi-class Label Noise Learning via Loss Decomposition and Centroid Estimation
In real-world scenarios, many large-scale datasets often contain inaccur...
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03/17/2022
On Vision Features in Multimodal Machine Translation
Previous work on multimodal machine translation (MMT) has focused on the...
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03/16/2022
Monte Carlo PINNs: deep learning approach for forward and inverse problems involving high dimensional fractional partial differential equations
We introduce a sampling based machine learning approach, Monte Carlo phy...
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02/10/2022
Consistency and Diversity induced Human Motion Segmentation
Subspace clustering is a classical technique that has been widely used f...
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11/27/2021
Quantifying human mixing patterns in Chinese provinces outside Hubei after the 2020 lockdown was lifted
Contact patterns play a key role in the spread of respiratory infectious...
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11/08/2021
threaTrace: Detecting and Tracing Host-based Threats in Node Level Through Provenance Graph Learning
Host-based threats such as Program Attack, Malware Implantation, and Adv...
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09/22/2021
The NiuTrans Machine Translation Systems for WMT21
This paper describes NiuTrans neural machine translation systems of the ...
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09/14/2021
Information Cocoons in Online Navigation
Social media and online navigation bring us enjoyable experience in acce...
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08/30/2021
Normalizing field flows: Solving forward and inverse stochastic differential equations using physics-informed flow models
We introduce in this work the normalizing field flows (NFF) for learning...
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08/18/2021
Specificity-preserving RGB-D Saliency Detection
RGB-D saliency detection has attracted increasing attention, due to its ...
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08/03/2021
A well-conditioned direct PinT algorithm for first- and second-order evolutionary equations
In this paper, we propose a direct parallel-in-time (PinT) algorithm for...
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06/28/2021
An augmented Lagrangian deep learning method for variational problems with essential boundary conditions
This paper is concerned with a novel deep learning method for variationa...
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05/26/2021
Context-aware Cross-level Fusion Network for Camouflaged Object Detection
Camouflaged object detection (COD) is a challenging task due to the low ...
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04/13/2021
Optimal design for kernel interpolation: applications to uncertainty quantification
The paper is concerned with classic kernel interpolation methods, in add...
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04/13/2021
An acceleration strategy for randomize-then-optimize sampling via deep neural networks
Randomize-then-optimize (RTO) is widely used for sampling from posterior...
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04/13/2021
Stein variational gradient descent with local approximations
Bayesian computation plays an important role in modern machine learning ...
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04/06/2021
ODE Transformer: An Ordinary Differential Equation-Inspired Model for Neural Machine Translation
It has been found that residual networks are an Euler discretization of ...
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03/25/2021
Quantifying the efficacy of childcare services on women employment
Women are set back in the labor market after becoming mother. Intuitivel...
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03/14/2021
Collaborative Filtering Approach to Link Prediction
Link prediction is a fundamental challenge in network science. Among var...
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02/23/2021
Progresses and Challenges in Link Prediction
Link prediction is a paradigmatic problem in network science, which aims...
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02/09/2021
Stability implies robust convergence of a class of diagonalization-based iterative algorithms
Solving wave equations in a time-parallel manner is challenging, and the...
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02/09/2021
A new discrete energy technique for multi-step backward difference formulas
The backward differentiation formula (BDF) is a useful family of implici...
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12/19/2020
An energy stable and maximum bound preserving scheme with variable time steps for time fractional Allen-Cahn equation
In this work, we propose a Crank-Nicolson-type scheme with variable step...
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12/12/2020
Improving EEG Decoding via Clustering-based Multi-task Feature Learning
Accurate electroencephalogram (EEG) pattern decoding for specific mental...
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12/07/2020
High resolution functional imaging through Lorentz transmission electron microscopy and differentiable programming
Lorentz transmission electron microscopy is a unique characterization te...
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11/26/2020
Positive definiteness of real quadratic forms resulting from the variable-step approximation of convolution operators
The positive definiteness of real quadratic forms with convolution struc...
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10/10/2020
Light Field Salient Object Detection: A Review and Benchmark
Salient object detection (SOD) is a long-standing research topic in comp...
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09/22/2020
Dynamic Fusion based Federated Learning for COVID-19 Detection
Medical diagnostic image analysis (e.g., CT scan or X-Ray) using machine...
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08/23/2020
Sparse approximation of data-driven Polynomial Chaos expansions: an induced sampling approach
One of the open problems in the field of forward uncertainty quantificat...
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08/07/2020
Analysis of the second order BDF scheme with variable steps for the molecular beam epitaxial model without slope selection
In this work, we are concerned with the stability and convergence analys...
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08/01/2020
