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A Multiscale Graph Convolutional Network for Change Detection in Homogeneous and Heterogeneous Remote Sensing Images
Change detection (CD) in remote sensing images has been an ever-expandin...
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Cross-Modal Contrastive Learning for Text-to-Image Generation
The output of text-to-image synthesis systems should be coherent, clear,...
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Modeling Heterogeneous Statistical Patterns in High-dimensional Data by Adversarial Distributions: An Unsupervised Generative Framework
Since the label collecting is prohibitive and time-consuming, unsupervis...
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Transfer learning of chaotic systems
Can a neural network trained by the time series of system A be used to p...
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ERNIE-Gram: Pre-Training with Explicitly N-Gram Masked Language Modeling for Natural Language Understanding
Coarse-grained linguistic information, such as name entities or phrases,...
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PseudoSeg: Designing Pseudo Labels for Semantic Segmentation
Recent advances in semi-supervised learning (SSL) demonstrate that a com...
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Co-evolution of Functional Brain Network at Multiple Scales during Early Infancy
The human brains are organized into hierarchically modular networks faci...
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GloDyNE: Global Topology Preserving Dynamic Network Embedding
Learning low-dimensional topological representation of a network in dyna...
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Improving NER's Performance with Massive financial corpus
Training large deep neural networks needs massive high quality annotatio...
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From Spectrum Wavelet to Vertex Propagation: Graph Convolutional Networks Based on Taylor Approximation
Graph convolutional networks (GCN) have been recently applied to semi-su...
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A Hybrid Evolutionary Algorithm for Reliable Facility Location Problem
The reliable facility location problem (RFLP) is an important research t...
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Image Augmentations for GAN Training
Data augmentations have been widely studied to improve the accuracy and ...
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Towards Personalized and Semantic Retrieval: An End-to-End Solution for E-commerce Search via Embedding Learning
Nowadays e-commerce search has become an integral part of many people's ...
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Towards Personalized and Semantic Retrieval: An End-to-EndSolution for E-commerce Search via Embedding Learning
Nowadays e-commerce search has become an integral part of many people's ...
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How Does COVID-19 impact Students with Disabilities/Health Concerns?
The impact of COVID-19 on students has been enormous, with an increase i...
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A Simple Semi-Supervised Learning Framework for Object Detection
Semi-supervised learning (SSL) has promising potential for improving the...
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Solving Missing-Annotation Object Detection with Background Recalibration Loss
This paper focuses on a novel and challenging detection scenario: A majo...
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Improved Consistency Regularization for GANs
Recent work has increased the performance of Generative Adversarial Netw...
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ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation
Current pre-training works in natural language generation pay little att...
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FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
Semi-supervised learning (SSL) provides an effective means of leveraging...
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MANELA: A Multi-Agent Algorithm for Learning Network Embeddings
Playing an essential role in data mining, machine learning has a long hi...
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Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models
We introduce a new local sparse attention layer that preserves two-dimen...
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ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring
We improve the recently-proposed "MixMatch" semi-supervised learning alg...
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Small-GAN: Speeding Up GAN Training Using Core-sets
Recent work by Brock et al. (2018) suggests that Generative Adversarial ...
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Consistency Regularization for Generative Adversarial Networks
Generative Adversarial Networks (GANs) are known to be difficult to trai...
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Combinatorial Losses through Generalized Gradients of Integer Linear Programs
When samples have internal structure, we often see a mismatch between th...
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IEG: Robust Neural Network Training to Tackle Severe Label Noise
Collecting large-scale data with clean labels for supervised training of...
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Distributed Equivalent Substitution Training for Large-Scale Recommender Systems
We present Distributed Equivalent Substitution (DES) training, a novel d...
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Building change detection based on multi-scale filtering and grid partition
Building change detection is of great significance in high resolution re...
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Multiple instance dense connected convolution neural network for aerial image scene classification
With the development of deep learning, many state-of-the-art natural ima...
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Approximation Capabilities of Neural Ordinary Differential Equations
Neural Ordinary Differential Equations have been recently proposed as an...
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DynWalks: Global Topology and Recent Changes Awareness Dynamic Network Embedding
Learning topological representation of a network in dynamic environments...
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Brain Network Construction and Classification Toolbox (BrainNetClass)
Brain functional network has become an increasingly used approach in und...
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ERNIE: Enhanced Representation through Knowledge Integration
We present a novel language representation model enhanced by knowledge c...
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Deep Learning for Signal Demodulation in Physical Layer Wireless Communications: Prototype Platform, Open Dataset, and Analytics
In this paper, we investigate deep learning (DL)-enabled signal demodula...
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MIMO Channel Interpolation via Tucker Decomposed Extreme Learning Machine
Channel interpolation is an essential technique for providing high-accur...
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A Unified Mammogram Analysis Method via Hybrid Deep Supervision
Automatic mammogram classification and mass segmentation play a critical...
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Deep Chronnectome Learning via Full Bidirectional Long Short-Term Memory Networks for MCI Diagnosis
Brain functional connectivity (FC) extracted from resting-state fMRI (RS...
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Self-Attention Generative Adversarial Networks
In this paper, we propose the Self-Attention Generative Adversarial Netw...
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Improving GANs Using Optimal Transport
We present Optimal Transport GAN (OT-GAN), a variant of generative adver...
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AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
In this paper, we propose an Attentional Generative Adversarial Network ...
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StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks
Although Generative Adversarial Networks (GANs) have shown remarkable su...
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Link the head to the "beak": Zero Shot Learning from Noisy Text Description at Part Precision
In this paper, we study learning visual classifiers from unstructured te...
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SegAN: Adversarial Network with Multi-scale L_1 Loss for Medical Image Segmentation
Inspired by classic generative adversarial networks (GAN), we propose a ...
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StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks
Synthesizing high-quality images from text descriptions is a challenging...
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Multi-lingual Geoparsing based on Machine Translation
Our method for multi-lingual geoparsing uses monolingual tools and resou...
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