
Datadriven model for hydraulic fracturing design optimization. Part II: Inverse problem
We describe a stacked model for predicting the cumulative fluid producti...
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A Differentiable Language Model Adversarial Attack on Text Classifiers
Robustness of huge Transformerbased models for natural language process...
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3D Parametric Wireframe Extraction Based on Distance Fields
We present a pipeline for parametric wireframe extraction from densely s...
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Adversarial Attacks on Deep Models for Financial Transaction Records
Machine learning models using transaction records as inputs are popular ...
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Manifold Topology Divergence: a Framework for Comparing Data Manifolds
We develop a framework for comparing data manifolds, aimed, in particula...
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Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein2 Benchmark
Despite the recent popularity of neural networkbased solvers for optima...
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LargeScale Wasserstein Gradient Flows
Wasserstein gradient flows provide a powerful means of understanding and...
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Towards Unpaired Depth Enhancement and SuperResolution in the Wild
Depth maps captured with commodity sensors are often of low quality and ...
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COHORTNEY: Deep Clustering for Heterogeneous Event Sequences
There is emerging attention towards working with event sequences. In par...
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Continuous Wasserstein2 Barycenter Estimation without Minimax Optimization
Wasserstein barycenters provide a geometric notion of the weighted avera...
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Denoising Score Matching with Random Fourier Features
The density estimation is one of the core problems in statistics. Despit...
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Topological obstructions in neural networks learning
We apply methods of topological data analysis to loss functions to gain ...
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Relightable 3D Head Portraits from a Smartphone Video
In this work, a system for creating a relightable 3D portrait of a human...
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AIenabled Prediction of eSports Player Performance Using the Data from Heterogeneous Sensors
The emerging progress of eSports lacks the tools for ensuring highquali...
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Towards PartBased Understanding of RGBD Scans
Recent advances in 3D semantic scene understanding have shown impressive...
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DEF: Deep Estimation of Sharp Geometric Features in 3D Shapes
Sharp feature lines carry essential information about humanmade objects...
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How Good MVSNets Are at Depth Fusion
We study the effects of the additional input to deep multiview stereo m...
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Detecting Video Game Player Burnout with the Use of Sensor Data and Machine Learning
Current research in eSports lacks the tools for proper game practising a...
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Random Fourier Features based SLAM
This work is dedicated to simultaneous continuoustime trajectory estima...
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Machine learning for recovery factor estimation of an oil reservoir: a tool for derisking at a hydrocarbon asset evaluation
Well known oil recovery factor estimation techniques such as analogy, vo...
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Towards forecast techniques for business analysts of large commercial data sets using matrix factorization methods
This research article suggests that there are significant benefits in ex...
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Topologybased Clusterwise Regression for User Segmentation and Demand Forecasting
Topological Data Analysis (TDA) is a recent approach to analyze data set...
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Graph Neural Networks for Model Recommendation using Time Series Data
Time series prediction aims to predict future values to help stakeholder...
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Addressing Cold Start in Recommender Systems with Hierarchical Graph Neural Networks
Recommender systems have become an essential instrument in a wide range ...
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Topological Data Analysis for Portfolio Management of Cryptocurrencies
Portfolio management is essential for any investment decision. Yet, trad...
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An industry case of largescale demand forecasting of hierarchical components
Demand forecasting of hierarchical components is essential in manufactur...
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DeepFolio: Convolutional Neural Networks for Portfolios with Limit Order Book Data
This work proposes DeepFolio, a new model for deep portfolio management ...
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Geometric Attention for Prediction of Differential Properties in 3D Point Clouds
Estimation of differential geometric quantities in discrete 3D data repr...
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Making DensePose fast and light
DensePose estimation task is a significant step forward for enhancing us...
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Latent Video Transformer
The video generation task can be formulated as a prediction of future vi...
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Multifidelity Neural Architecture Search with Knowledge Distillation
Neural architecture search (NAS) targets at finding the optimal architec...
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NASBenchNLP: Neural Architecture Search Benchmark for Natural Language Processing
Neural Architecture Search (NAS) is a promising and rapidly evolving res...
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Recurrent Convolutional Neural Networks help to predict location of Earthquakes
We examine the applicability of modern neural network architectures to t...
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Bayesian Sparsification Methods for Deep Complexvalued Networks
With continual miniaturization ever more applications of deep learning c...
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Datadriven models and computational tools for neurolinguistics: a language technology perspective
In this paper, our focus is the connection and influence of language tec...
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Software System for Road Condition Forecast Correction
In this paper, we present a monitoring system that allows increasing roa...
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Deep Vectorization of Technical Drawings
We present a new method for vectorization of technical line drawings, su...
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Gradientbased adversarial attacks on categorical sequence models via traversing an embedded world
An adversarial attack paradigm explores various scenarios for vulnerabil...
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Reinforcement Learning for Combinatorial Optimization: A Survey
Combinatorial optimization (CO) is the workhorse of numerous important a...
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Integral Mixabilty: a Tool for Efficient Online Aggregation of Functional and Probabilistic Forecasts
In this paper we extend the setting of the online prediction with expert...
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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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Tensor Completion via Gaussian Process Based Initialization
In this paper, we consider the tensor completion problem representing th...
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Barcodes as summary of objective function's topology
We apply the canonical forms (barcodes) of gradient Morse complexes to e...
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3D Deformable Convolutions for MRI classification
Deep learning convolutional neural networks have proved to be a powerful...
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Weakly Supervised Fine Tuning Approach for Brain Tumor Segmentation Problem
Segmentation of tumors in brain MRI images is a challenging task, where ...
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Understanding Isomorphism Bias in Graph Data Sets
In recent years there has been a rapid increase in classification method...
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Wasserstein2 Generative Networks
Modern generative learning is mainly associated with Generative Adversar...
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BooVAE: A scalable framework for continual VAE learning under boosting approach
Variational Auto Encoders (VAE) are capable of generating realistic imag...
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Understanding Cyber Athletes Behaviour Through a Smart Chair: CS:GO and Monolith Team Scenario
eSports is the rapidly developing multidisciplinary domain. However, res...
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Sensors and Game Synchronization for Data Analysis in eSports
eSports industry has greatly progressed within the last decade in terms ...
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Evgeny Burnaev
verfied profile
Associate Professor for Center for Computational and DataIntensive Science and Engineering