
Negational Symmetry of Quantum Neural Networks for Binary Pattern Classification
Entanglement is a physical phenomenon, which has fueled recent successes...
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Reconsidering Representation Alignment for Multiview Clustering
Aligning distributions of view representations is a core component of to...
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Joint Optimization of an Autoencoder for Clustering and Embedding
Incorporating kmeanslike clustering techniques into (deep) autoencoder...
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Towards Robust Medical Image Segmentation on SmallScale Data with Incomplete Labels
The datadriven nature of deep learning models for semantic segmentation...
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SCGNet: SelfConstructing Graph Neural Networks for Semantic Segmentation
Capturing global contextual representations by exploiting longrange pix...
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Multiview SelfConstructing Graph Convolutional Networks with Adaptive Class Weighting Loss for Semantic Segmentation
We propose a novel architecture called the Multiview SelfConstructing ...
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CodeAligned Autoencoders for Unsupervised Change Detection in Multimodal Remote Sensing Images
Image translation with convolutional autoencoders has recently been used...
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SelfConstructing Graph Convolutional Networks for Semantic Labeling
Graph Neural Networks (GNNs) have received increasing attention in many ...
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Dense Dilated Convolutions Merging Network for Land Cover Classification
Land cover classification of remote sensing images is a challenging task...
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Deep Image Translation with an AffinityBased Change Prior for Unsupervised Multimodal Change Detection
Image translation with convolutional neural networks has recently been u...
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Information Plane Analysis of Deep Neural Networks via MatrixBased Renyi's Entropy and Tensor Kernels
Analyzing deep neural networks (DNNs) via information plane (IP) theory ...
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Road Mapping In LiDAR Images Using A JointTask Dense Dilated Convolutions Merging Network
It is important, but challenging, for the forest industry to accurately ...
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Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images
We propose a network for semantic mapping called the Dense Dilated Convo...
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Learning Latent Representations of Bank Customers With The Variational Autoencoder
Learning data representations that reflect the customers' creditworthine...
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Deep DivergenceBased Approach to Clustering
A promising direction in deep learning research consists in learning rep...
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Recurrent Deep Divergencebased Clustering for simultaneous feature learning and clustering of variable length time series
The task of clustering unlabeled time series and sequences entails a par...
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Reinforced AutoZoom Net: Towards Accurate and Fast Breast Cancer Segmentation in Wholeslide Images
Convolutional neural networks have led to significant breakthroughs in t...
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The Deep Kernelized Autoencoder
Autoencoders learn data representations (codes) in such a way that the i...
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QueryConditioned ThreePlayer Adversarial Network for Video Summarization
Video summarization plays an important role in video understanding by se...
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Uncertainty and Interpretability in Convolutional Neural Networks for Semantic Segmentation of Colorectal Polyps
Convolutional Neural Networks (CNNs) are propelling advances in a range ...
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Geometric Generalization Based ZeroShot Learning Dataset Infinite World: Simple Yet Powerful
Raven's Progressive Matrices are one of the widely used tests in evaluat...
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Unsupervised Domain Adaptation for Automatic Estimation of Cardiothoracic Ratio
The cardiothoracic ratio (CTR), a clinical metric of heart size in chest...
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SegmentBased Credit Scoring Using Latent Clusters in the Variational Autoencoder
Identifying customer segments in retail banking portfolios with differen...
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Rethinking Knowledge Graph Propagation for ZeroShot Learning
The potential of graph convolutional neural networks for the task of zer...
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Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders
Learning compressed representations of multivariate time series (MTS) fa...
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DTRGAN: Dilated Temporal Relational Adversarial Network for Video Summarization
The large amount of videos popping up every day, make it is more and mor...
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ConnNet: A LongRange RelationAware PixelConnectivity Network for Salient Segmentation
Salient segmentation aims to segment out attentiongrabbing regions, a c...
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Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks
Clinical measurements that can be represented as time series constitute ...
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Urban Land Cover Classification with Missing Data Using Deep Convolutional Neural Networks
Automatic urban land cover classification is a classical problem in remo...
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Deep Kernelized Autoencoders
In this paper we introduce the deep kernelized autoencoder, a neural net...
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Temporal Overdrive Recurrent Neural Network
In this work we present a novel recurrent neural network architecture de...
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Michael Kampffmeyer
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