
3D Deformable Convolutions for MRI classification
Deep learning convolutional neural networks have proved to be a powerful...
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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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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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LatentSpace Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds
Constructing highquality generative models for 3D shapes is a fundament...
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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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Procedural Synthesis of Remote Sensing Images for Robust Change Detection with Neural Networks
Datadriven methods such as convolutional neural networks (CNNs) are kno...
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Monocular 3D Object Detection via Geometric Reasoning on Keypoints
Monocular 3D object detection is wellknown 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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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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Model Selection for Anomaly Detection
Anomaly detection based on oneclass classification algorithms is broadl...
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Influence of Resampling on Accuracy of Imbalanced Classification
In many realworld binary classification tasks (e.g. detection of certai...
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Inductive Conformal Martingales for ChangePoint Detection
We consider the problem of quickest changepoint detection in data strea...
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Conformal kNN Anomaly Detector for Univariate Data Streams
Anomalies in timeseries data give essential and often actionable inform...
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Machine Learning in Appearancebased Robot Selflocalization
An appearancebased robot selflocalization problem is considered in the...
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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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OneClass SVM with Privileged Information and its Application to Malware Detection
A number of important applied problems in engineering, finance and medic...
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Conformalized Kernel Ridge Regression
General predictive models do not provide a measure of confidence in pred...
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Conformalized density and distancebased anomaly detection in timeseries data
Anomalies (unusual patterns) in timeseries data give essential, and oft...
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LargeScale Shape Retrieval with Sparse 3D Convolutional Neural Networks
In this paper we present results of performance evaluation of S3DCNN  a...
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Automatic Construction of a Recurrent Neural Network based Classifier for Vehicle Passage Detection
Recurrent Neural Networks (RNNs) are extensively used for timeseries mo...
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Efficiency of conformalized ridge regression
Conformal prediction is a method of producing prediction sets that can b...
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Steganographic Generative Adversarial Networks
Steganography is collection of methods to hide secret information ("payl...
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Quadraturebased features for kernel approximation
We consider the problem of improving kernel approximation via randomized...
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Satellite imagery analysis for operational damage assessment in Emergency situations
When major disaster occurs the questions are raised how to estimate the ...
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Driving Digital Rock towards Machine Learning: predicting permeability with Gradient Boosting and Deep Neural Networks
We present a research study aimed at testing of applicability of machine...
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On One Problem in Multichannel Signal Detection
We consider a statistical problem of detection of a signal with unknown ...
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Anonymous Walk Embeddings
The task of representing entire graphs has seen a surge of prominent res...
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Aggregating Strategies for Longterm Forecasting
The article is devoted to investigating the application of aggregating a...
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Datadriven model for the identification of the rock type at a drilling bit
In order to bridge the gap of more than 15m between the drilling bit and...
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Machine Learning pipeline for discovering neuroimagingbased biomarkers in neurology and psychiatry
We consider a problem of diagnostic pattern recognition/classification f...
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fMRI: preprocessing, classification and pattern recognition
As machine learning continues to gain momentum in the neuroscience commu...
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Laplace Inference for Multifidelity Gaussian Process Classification
In this paper we address a classification problem where two sources of l...
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GTApprox: surrogate modeling for industrial design
We describe GTApprox  a new tool for mediumscale surrogate modeling in...
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Targeted change detection in remote sensing images
Recent developments in the remote sensing systems and image processing m...
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Gradient Boosting to Boost the Efficiency of Hydraulic Fracturing
In this paper we present a datadriven model for forecasting the product...
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Reconstruction of 3D Porous Media From 2D Slices
We propose a novel deep learning architecture for threedimensional poro...
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Adaptive Hedging under Delayed Feedback
The article is devoted to investigating the application of hedging strat...
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Esports Athletes and Players: a Comparative Study
We present a comparative study of the players' and professional athletes...
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Realtime datadriven detection of the rock type alteration during a directional drilling
During the directional drilling, a bit may sometimes go to a nonproducti...
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UserControllable MultiTexture Synthesis with Generative Adversarial Networks
We propose a novel multitexture synthesis model based on generative adv...
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ABC: A Big CAD Model Dataset For Geometric Deep Learning
We introduce ABCDataset, a collection of one million ComputerAided Des...
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A Predictive Model for SteadyState Multiphase Pipe Flow: Machine Learning on Lab Data
Engineering simulators used for steadystate multiphase pipe flows are c...
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MaxEntropy Pursuit Variational Inference
One of the core problems in variational inference is a choice of approxi...
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Artificial Neural Network Surrogate Modeling of Oil Reservoir: a Case Study
We develop a datadriven model, introducing recent advances in machine l...
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Demand forecasting techniques for buildtoorder lean manufacturing supply chains
Buildtoorder (BTO) supply chains have become commonplace in industrie...
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Ensemble of 3D CNN regressors with data fusion for fluid intelligence prediction
In this work, we aim at predicting children's fluid intelligence scores ...
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Rare Failure Prediction via Event Matching for Aerospace Applications
In this paper, we consider a problem of failure prediction in the contex...
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Perceptual deep depth superresolution
RGBD images, combining highresolution color and lowerresolution depth ...
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Visual Fixations Duration as an Indicator of Skill Level in eSports
Using highly interactive systems like computer games requires a lot of v...
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Evgeny Burnaev
verfied profile
Associate Professor for Center for Computational and DataIntensive Science and Engineering