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Hyperbolic Image Embeddings
Computer vision tasks such as image classification, image retrieval and ...
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Perceptually-based single-image depth super-resolution
RGBD images, combining high-resolution color and lower-resolution depth ...
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Instance Segmentation of Biological Images Using Harmonic Embeddings
We present a new instance segmentation approach tailored to biological i...
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Stochastic gradient algorithms from ODE splitting perspective
We present a different view on stochastic optimization, which goes back ...
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Tensor Completion via Gaussian Process Based Initialization
In this paper, we consider the tensor completion problem representing th...
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Real-world attack on MTCNN face detection system
Recent studies proved that deep learning approaches achieve remarkable r...
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Deep Neural Networks Predicting Oil Movement in a Development Unit
We present a novel technique for assessing the dynamics of multiphase fl...
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Interpolated Adjoint Method for Neural ODEs
In this paper, we propose a method, which allows us to alleviate or comp...
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Adversarial point set registration
We present a novel approach to point set registration which is based on ...
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Latent-Space Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds
Constructing high-quality generative models for 3D shapes is a fundament...
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Generalized Tensor Models for Recurrent Neural Networks
Recurrent Neural Networks (RNNs) are very successful at solving challeng...
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Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems
Automatic segmentation methods based on deep learning have recently demo...
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Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network
Most state of the art deep neural networks are overparameterized and exh...
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Tumor Delineation For Brain Radiosurgery by a ConvNet and Non-Uniform Patch Generation
Deep learning methods are actively used for brain lesion segmentation. O...
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Tensorized Transformer for Dynamical Systems Modeling
The identification of nonlinear dynamics from observations is essential ...
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Image Manipulation with Perceptual Discriminators
Systems that perform image manipulation using deep convolutional network...
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Universality Theorems for Generative Models
Despite the fact that generative models are extremely successful in prac...
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Keypoints Localization for Joint Vertebra Detection and Fracture Severity Quantification
Vertebral body compression fractures are reliable early signs of osteopo...
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Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection
Midline shift (MLS) is a well-established factor used for outcome predic...
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Rapid seismic domain transfer: Seismic velocity inversion and modeling using deep generative neural networks
Traditional physics-based approaches to infer sub-surface properties suc...
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Procedural Synthesis of Remote Sensing Images for Robust Change Detection with Neural Networks
Data-driven methods such as convolutional neural networks (CNNs) are kno...
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Empirical study of extreme overfitting points of neural networks
In this paper we propose a method of obtaining points of extreme overfit...
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Bayesian aggregation improves traditional single image crop classification approaches
Machine learning (ML) methods and neural networks (NN) are widely implem...
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Towards Understanding Normalization in Neural ODEs
Normalization is an important and vastly investigated technique in deep ...
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Monocular 3D Object Detection via Geometric Reasoning on Keypoints
Monocular 3D object detection is well-known to be a challenging vision t...
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Boundary Loss for Remote Sensing Imagery Semantic Segmentation
In response to the growing importance of geospatial data, its analysis i...
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Stereo relative pose from line and point feature triplets
Stereo relative pose problem lies at the core of stereo visual odometry ...
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Deep Image Prior
Deep convolutional networks have become a popular tool for image generat...
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Universal Denoising Networks : A Novel CNN-based Network Architecture for Image Denoising
We design a novel network architecture for learning discriminative image...
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Long-Term Sequential Prediction Using Expert Advice
For the prediction with expert advice setting, we consider methods to co...
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Quantified advantage of discontinuous weight selection in approximations with deep neural networks
We consider approximations of 1D Lipschitz functions by deep ReLU networ...
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Art of singular vectors and universal adversarial perturbations
Vulnerability of Deep Neural Networks (DNNs) to adversarial attacks has ...
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Simultaneous Matrix Diagonalization for Structural Brain Networks Classification
This paper considers the problem of brain disease classification based o...
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Error bounds for approximations with deep ReLU networks
We study expressive power of shallow and deep neural networks with piece...
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Forecasting of commercial sales with large scale Gaussian Processes
This paper argues that there has not been enough discussion in the field...
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Large Scale Variable Fidelity Surrogate Modeling
Engineers widely use Gaussian process regression framework to construct ...
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Inductive Conformal Martingales for Change-Point Detection
We consider the problem of quickest change-point detection in data strea...
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Conformal k-NN Anomaly Detector for Univariate Data Streams
Anomalies in time-series data give essential and often actionable inform...
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Representation Learning and Pairwise Ranking for Implicit Feedback in Recommendation Systems
In this paper, we propose a novel ranking framework for collaborative fi...
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Non-Local Color Image Denoising with Convolutional Neural Networks
We propose a novel deep network architecture for grayscale and color ima...
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It Takes (Only) Two: Adversarial Generator-Encoder Networks
We present a new autoencoder-type architecture that is trainable in an u...
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Machine Learning in Appearance-based Robot Self-localization
An appearance-based robot self-localization problem is considered in the...
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Efficient Rectangular Maximal-Volume Algorithm for Rating Elicitation in Collaborative Filtering
Cold start problem in Collaborative Filtering can be solved by asking ne...
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Escape from Cells: Deep Kd-Networks for the Recognition of 3D Point Cloud Models
We present a new deep learning architecture (called Kd-network) that is ...
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Minimax Error of Interpolation and Optimal Design of Experiments for Variable Fidelity Data
Engineering problems often involve data sources of variable fidelity wit...
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Steganographic Generative Adversarial Networks
Steganography is collection of methods to hide secret information ("payl...
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Conformalized density- and distance-based anomaly detection in time-series data
Anomalies (unusual patterns) in time-series data give essential, and oft...
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Fifty Shades of Ratings: How to Benefit from a Negative Feedback in Top-N Recommendations Tasks
Conventional collaborative filtering techniques treat a top-n recommenda...
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Residual and Plain Convolutional Neural Networks for 3D Brain MRI Classification
In the recent years there have been a number of studies that applied dee...
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Improved Texture Networks: Maximizing Quality and Diversity in Feed-forward Stylization and Texture Synthesis
The recent work of Gatys et al., who characterized the style of an image...
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