b'Skoltech'

research

∙ 04/03/2019

Hyperbolic Image Embeddings

Computer vision tasks such as image classification, image retrieval and ...

Valentin Khrulkov, et al. ∙

research

∙ 03/27/2021

Automatic differentiation for Riemannian optimization on low-rank matrix and tensor-train manifolds

In scientific computing and machine learning applications, matrices and ...

Alexander Novikov, et al. ∙

research

∙ 12/24/2018

Perceptually-based single-image depth super-resolution

RGBD images, combining high-resolution color and lower-resolution depth ...

O. Voinov, et al. ∙

research

∙ 04/10/2019

Instance Segmentation of Biological Images Using Harmonic Embeddings

We present a new instance segmentation approach tailored to biological i...

Victor Kulikov, et al. ∙

research

∙ 04/19/2020

Stochastic gradient algorithms from ODE splitting perspective

We present a different view on stochastic optimization, which goes back ...

Daniil Merkulov, et al. ∙

research

∙ 07/30/2021

Surrogate Modelling for Injection Molding Processes using Machine Learning

Injection molding is one of the most popular manufacturing methods for t...

Arsenii Uglov, et al. ∙

research

∙ 12/11/2019

Tensor Completion via Gaussian Process Based Initialization

In this paper, we consider the tensor completion problem representing th...

Yermek Kapushev, et al. ∙

research

∙ 10/14/2019

Real-world attack on MTCNN face detection system

Recent studies proved that deep learning approaches achieve remarkable r...

Edgar Kaziakhmedov, et al. ∙

research

∙ 04/14/2022

Interpretable Vertebral Fracture Quantification via Anchor-Free Landmarks Localization

Vertebral body compression fractures are early signs of osteoporosis. Th...

Alexey Zakharov, et al. ∙

research

∙ 10/16/2021

Automated Remote Sensing Forest Inventory Using Satelite Imagery

For many countries like Russia, Canada, or the USA, a robust and detaile...

Abduragim Shtanchaev, et al. ∙

research

∙ 01/08/2019

Deep Neural Networks Predicting Oil Movement in a Development Unit

We present a novel technique for assessing the dynamics of multiphase fl...

Pavel Temirchev, et al. ∙

research

∙ 03/11/2020

Interpolated Adjoint Method for Neural ODEs

In this paper, we propose a method, which allows us to alleviate or comp...

Talgat Daulbaev, et al. ∙

research

∙ 07/22/2021

MobileCharger: an Autonomous Mobile Robot with Inverted Delta Actuator for Robust and Safe Robot Charging

MobileCharger is a novel mobile charging robot with an Inverted Delta ac...

Iaroslav Okunevich, et al. ∙

research

∙ 11/20/2018

Adversarial point set registration

We present a novel approach to point set registration which is based on ...

Sergei Divakov, et al. ∙

research

∙ 12/13/2019

Latent-Space Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds

Constructing high-quality generative models for 3D shapes is a fundament...

Vage Egiazarian, et al. ∙

research

∙ 04/21/2021

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

This paper reviews the first NTIRE challenge on quality enhancement of c...

Ren Yang, et al. ∙

research

∙ 08/05/2021

DeepScanner: a Robotic System for Automated 2D Object Dataset Collection with Annotations

In the proposed study, we describe the possibility of automated dataset ...

Valery Ilin, et al. ∙

research

∙ 12/21/2021

Can We Use Neural Regularization to Solve Depth Super-Resolution?

Depth maps captured with commodity sensors often require super-resolutio...

Milena Gazdieva, et al. ∙

research

∙ 01/30/2019

Generalized Tensor Models for Recurrent Neural Networks

Recurrent Neural Networks (RNNs) are very successful at solving challeng...

Valentin Khrulkov, et al. ∙

research

∙ 08/15/2019

Bayesian Generative Models for Knowledge Transfer in MRI Semantic Segmentation Problems

Automatic segmentation methods based on deep learning have recently demo...

Anna Kuzina, et al. ∙

research

∙ 06/06/2022

Scan2Part: Fine-grained and Hierarchical Part-level Understanding of Real-World 3D Scans

We propose Scan2Part, a method to segment individual parts of objects in...

Alexandr Notchenko, et al. ∙

research

∙ 06/20/2022

Studying the role of named entities for content preservation in text style transfer

Text style transfer techniques are gaining popularity in Natural Languag...

Nikolay Babakov, et al. ∙

research

∙ 08/12/2020

Stable Low-rank Tensor Decomposition for Compression of Convolutional Neural Network

Most state of the art deep neural networks are overparameterized and exh...

Anh-Huy Phan, et al. ∙

research

∙ 07/22/2021

DeltaCharger: Charging Robot with Inverted Delta Mechanism and CNN-driven High Fidelity Tactile Perception for Precise 3D Positioning

DeltaCharger is a novel charging robot with an Inverted Delta structure ...

Iaroslav Okunevich, et al. ∙

research

∙ 08/01/2018

Tumor Delineation For Brain Radiosurgery by a ConvNet and Non-Uniform Patch Generation

Deep learning methods are actively used for brain lesion segmentation. O...

Egor Krivov, et al. ∙

research

∙ 06/05/2020

Tensorized Transformer for Dynamical Systems Modeling

The identification of nonlinear dynamics from observations is essential ...

Anna Shalova, et al. ∙

research

∙ 09/05/2018

Image Manipulation with Perceptual Discriminators

Systems that perform image manipulation using deep convolutional network...

Diana Sungatullina, et al. ∙

research

∙ 05/27/2019

Universality Theorems for Generative Models

Despite the fact that generative models are extremely successful in prac...

Valentin Khrulkov, et al. ∙

research

∙ 05/25/2020

Keypoints Localization for Joint Vertebra Detection and Fracture Severity Quantification

Vertebral body compression fractures are reliable early signs of osteopo...

Maxim Pisov, et al. ∙

research

∙ 03/04/2022

Beyond Plain Toxic: Detection of Inappropriate Statements on Flammable Topics for the Russian Language

Toxicity on the Internet, such as hate speech, offenses towards particul...

Nikolay Babakov, et al. ∙

research

∙ 08/13/2019

Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection

Midline shift (MLS) is a well-established factor used for outcome predic...

Maxim Pisov, et al. ∙

research

∙ 05/22/2018

Rapid seismic domain transfer: Seismic velocity inversion and modeling using deep generative neural networks

Traditional physics-based approaches to infer sub-surface properties suc...

Lukas Mosser, et al. ∙

research

∙ 05/20/2019

Procedural Synthesis of Remote Sensing Images for Robust Change Detection with Neural Networks

Data-driven methods such as convolutional neural networks (CNNs) are kno...

Maria Kolos, et al. ∙

research

∙ 06/14/2019

Empirical study of extreme overfitting points of neural networks

In this paper we propose a method of obtaining points of extreme overfit...

Daniil Merkulov, et al. ∙

research

∙ 04/07/2020

Bayesian aggregation improves traditional single image crop classification approaches

Machine learning (ML) methods and neural networks (NN) are widely implem...

Ivan Matvienko, et al. ∙

research

∙ 04/20/2020

Towards Understanding Normalization in Neural ODEs

Normalization is an important and vastly investigated technique in deep ...

Julia Gusak, et al. ∙

research

∙ 08/10/2021

Optimal MRI Undersampling Patterns for Ultimate Benefit of Medical Vision Tasks

To accelerate MRI, the field of compressed sensing is traditionally conc...

Artem Razumov, et al. ∙

research

∙ 09/16/2017

Forecasting of commercial sales with large scale Gaussian Processes

This paper argues that there has not been enough discussion in the field...

Rodrigo Rivera, et al. ∙

research

∙ 05/14/2019

Monocular 3D Object Detection via Geometric Reasoning on Keypoints

Monocular 3D object detection is well-known to be a challenging vision t...

Ivan Barabanau, et al. ∙

research

∙ 05/20/2019

Boundary Loss for Remote Sensing Imagery Semantic Segmentation

In response to the growing importance of geospatial data, its analysis i...

Alexey Bokhovkin, et al. ∙

research

∙ 06/29/2019

Stereo relative pose from line and point feature triplets

Stereo relative pose problem lies at the core of stereo visual odometry ...

Alexander Vakhitov, et al. ∙

research

∙ 11/29/2017

Deep Image Prior

Deep convolutional networks have become a popular tool for image generat...

Dmitry Ulyanov, et al. ∙

research

∙ 11/21/2017

Universal Denoising Networks : A Novel CNN-based Network Architecture for Image Denoising

We design a novel network architecture for learning discriminative image...

Stamatios Lefkimmiatis, et al. ∙

research

∙ 11/08/2017

Long-Term Sequential Prediction Using Expert Advice

For the prediction with expert advice setting, we consider methods to co...

Eugeny Burnaev, et al. ∙

research

∙ 05/03/2017

Quantified advantage of discontinuous weight selection in approximations with deep neural networks

We consider approximations of 1D Lipschitz functions by deep ReLU networ...

Dmitry Yarotsky, et al. ∙

research

∙ 09/11/2017

Art of singular vectors and universal adversarial perturbations

Vulnerability of Deep Neural Networks (DNNs) to adversarial attacks has ...

Valentin Khrulkov, et al. ∙

research

∙ 10/14/2017

Simultaneous Matrix Diagonalization for Structural Brain Networks Classification

This paper considers the problem of brain disease classification based o...

Nikita Mokrov, et al. ∙

research

∙ 10/03/2016

Error bounds for approximations with deep ReLU networks

We study expressive power of shallow and deep neural networks with piece...

Dmitry Yarotsky, et al. ∙

research

∙ 07/12/2017

Large Scale Variable Fidelity Surrogate Modeling

Engineers widely use Gaussian process regression framework to construct ...

Evgeny Burnaev, et al. ∙

research

∙ 06/11/2017

Inductive Conformal Martingales for Change-Point Detection

We consider the problem of quickest change-point detection in data strea...

Denis Volkhonskiy, et al. ∙

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