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08/27/2023
Bi-Modality Medical Image Synthesis Using Semi-Supervised Sequential Generative Adversarial Networks
In this paper, we propose a bi-modality medical image synthesis approach...
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06/19/2023
Dual-view Correlation Hybrid Attention Network for Robust Holistic Mammogram Classification
Mammogram image is important for breast cancer screening, and typically ...
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03/05/2023
MFAI: A Scalable Bayesian Matrix Factorization Approach to Leveraging Auxiliary Information
In various practical situations, matrix factorization methods suffer fro...
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12/29/2022
TensorFHE: Achieving Practical Computation on Encrypted Data Using GPGPU
In this paper, we propose TensorFHE, an FHE acceleration solution based ...
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11/26/2022
Robust One-shot Segmentation of Brain Tissues via Image-aligned Style Transformation
One-shot segmentation of brain tissues is typically a dual-model iterati...
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10/15/2022
Bidirectional Semi-supervised Dual-branch CNN for Robust 3D Reconstruction of Stereo Endoscopic Images via Adaptive Cross and Parallel Supervisions
Semi-supervised learning via teacher-student network can train a model e...
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06/05/2022
Accurate Scoliosis Vertebral Landmark Localization on X-ray Images via Shape-constrained Multi-stage Cascaded CNNs
Vertebral landmark localization is a crucial step for variant spine-rela...
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01/06/2022
A deep learning-based model reduction (DeePMR) method for simplifying chemical kinetics
A deep learning-based model reduction (DeePMR) method for simplifying ch...
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09/25/2021
Joint Progressive and Coarse-to-fine Registration of Brain MRI via Deformation Field Integration and Non-Rigid Feature Fusion
Registration of brain MRI images requires to solve a deformation field, ...
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08/16/2021
Deep Natural Language Processing for LinkedIn Search
Many search systems work with large amounts of natural language data, e....
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05/25/2021
An Upper Limit of Decaying Rate with Respect to Frequency in Deep Neural Network
Deep neural network (DNN) usually learns the target function from low to...
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12/06/2020
Fourier-domain Variational Formulation and Its Well-posedness for Supervised Learning
A supervised learning problem is to find a function in a hypothesis func...
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11/19/2020
Defocus Blur Detection via Salient Region Detection Prior
Defocus blur always occurred in photos when people take photos by Digita...
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08/31/2020
Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection
Discrete event sequences are ubiquitous, such as an ordered event series...
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05/27/2020
Chat as Expected: Learning to Manipulate Black-box Neural Dialogue Models
Recently, neural network based dialogue systems have become ubiquitous i...
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05/15/2020
Siamese Neural Networks for Class Activity Detection
Classroom activity detection (CAD) aims at accurately recognizing speake...
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02/20/2020
Graph Computing based Distributed State Estimation with PMUs
Power system state estimation plays a fundamental and critical role in t...
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11/22/2019
Learning Multi-level Dependencies for Robust Word Recognition
Robust language processing systems are becoming increasingly important g...
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11/08/2019
Two-stage WECC Composite Load Modeling: A Double Deep Q-Learning Networks Approach
With the increasing complexity of modern power systems, conventional dyn...
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09/23/2019
Automatic Short Answer Grading via Multiway Attention Networks
Automatic short answer grading (ASAG), which autonomously score student ...
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09/01/2019
Deep Knowledge Tracing with Side Information
Monitoring student knowledge states or skill acquisition levels known as...
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07/18/2019
Recommender Systems with Heterogeneous Side Information
In modern recommender systems, both users and items are associated with ...
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07/12/2019
R-Transformer: Recurrent Neural Network Enhanced Transformer
Recurrent Neural Networks have long been the dominating choice for seque...
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04/24/2019
Autonomous Voltage Control for Grid Operation Using Deep Reinforcement Learning
Modern power grids are experiencing grand challenges caused by the stoch...
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04/08/2019
A High-Performance Energy Management System based on Evolving Graph
As the fast growth and large integration of distributed generation, rene...
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03/29/2019
Graph Computing based Fast Screening in Contingency Analysis
During last decades, contingency analysis has been facing challenges fro...
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03/26/2019
Probabilistic Load Forecasting via Point Forecast Feature Integration
Short-term load forecasting is a critical element of power systems energ...
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03/26/2019
Short-term Load Forecasting at Different Aggregation Levels with Predictability Analysis
Short-term load forecasting (STLF) is essential for the reliable and eco...
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02/20/2019
Submodular Load Clustering with Robust Principal Component Analysis
Traditional load analysis is facing challenges with the new electricity ...
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02/19/2019
Graph Computing based Distributed Fast Decoupled Power Flow Analysis
Power flow analysis plays a fundamental and critical role in the energy ...
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12/17/2018
Semi-supervised mp-MRI Data Synthesis with StitchLayer and Auxiliary Distance Maximization
In this paper, we address the problem of synthesizing multi-parameter ma...
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11/29/2018
A Rprop-Neural-Network-Based PV Maximum Power Point Tracking Algorithm with Short-Circuit Current Limitation
This paper proposes a resilient-backpropagation-neural-network-(Rprop-NN...
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11/29/2018
A Neuron-Network-Based Optimal Control of Ultra-Capacitors with System Uncertainties
In this paper, a neural-network (NN)-based online optimal control method...
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10/25/2018
Graph Based Power Flow Calculation for Energy Management System
Power flow calculation in EMS is required to accommodate a large and com...
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09/18/2018
Power Market Price Forecasting via Deep Learning
A study on power market price forecasting by deep learning is presented....
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09/05/2018
Exploration of Bi-Level PageRank Algorithm for Power Flow Analysis Using Graph Database
Compared with traditional relational database, graph database, GDB, is a...
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09/05/2018
Power Flow Analysis Using Graph based Combination of Iterative Methods and Vertex Contraction Approach
Compared with relational database (RDB), graph database (GDB) is a more ...
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08/19/2018
Linked Recurrent Neural Networks
Recurrent Neural Networks (RNNs) have been proven to be effective in mod...
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03/15/2018
CIM/E Oriented Graph Database Model Architecture and Parallel Network Topology Processing
CIM/E is an easy and efficient electric power model exchange standard be...
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03/08/2018
Exploration of Graph Computing in Power System State Estimation
With the increased complexity of power systems due to the integration of...
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08/18/2017