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09/12/2023
Long-term drought prediction using deep neural networks based on geospatial weather data
The accurate prediction of drought probability in specific regions is cr...
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09/10/2023
Machine Translation Models Stand Strong in the Face of Adversarial Attacks
Adversarial attacks expose vulnerabilities of deep learning models by in...
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09/09/2023
Correcting sampling biases via importancereweighting for spatial modeling
In machine learning models, the estimation of errors is often complex du...
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08/22/2023
Designing an attack-defense game: how to increase robustness of financial transaction models via a competition
Given the escalating risks of malicious attacks in the finance sector an...
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08/22/2023
Uncertainty Estimation of Transformers' Predictions via Topological Analysis of the Attention Matrices
Determining the degree of confidence of deep learning model in its predi...
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08/20/2023
Hiding Backdoors within Event Sequence Data via Poisoning Attacks
The financial industry relies on deep learning models for making importa...
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08/15/2023
Portfolio Selection via Topological Data Analysis
Portfolio management is an essential part of investment decision-making....
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03/01/2023
Label Attention Network for sequential multi-label classification
Multi-label classification is a natural problem statement for sequential...
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02/13/2023
Continuous-time convolutions model of event sequences
Massive samples of event sequences data occur in various domains, includ...
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02/06/2023
Uncertainty estimation for time series forecasting via Gaussian process regression surrogates
Machine learning models are widely used to solve real-world problems in ...
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12/29/2022
Unsupervised construction of representations for oil wells via Transformers
Determining and predicting reservoir formation properties for newly dril...
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09/28/2022
Non-contrastive approaches to similarity learning: positive examples are all you need
The similarity learning problem in the oil & gas industry aims to constr...
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09/26/2022
Self-supervised similarity models based on well-logging data
Adopting data-based approaches leads to model improvement in numerous Oi...
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09/05/2022
ScaleFace: Uncertainty-aware Deep Metric Learning
The performance of modern deep learning-based systems dramatically depen...
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08/31/2022
QuantNAS for super resolution: searching for efficient quantization-friendly architectures against quantization noise
There is a constant need for high-performing and computationally efficie...
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06/27/2022
Effective training-time stacking for ensembling of deep neural networks
Ensembling is a popular and effective method for improving machine learn...
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06/27/2022
Transfer learning for ensembles: reducing computation time and keeping the diversity
Transferring a deep neural network trained on one problem to another req...
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04/18/2022
Usage of specific attention improves change point detection
The change point is a moment of an abrupt alteration in the data distrib...
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04/15/2022
Deep learning model solves change point detection for multiple change types
A change points detection aims to catch an abrupt disorder in data distr...
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02/24/2022
Embedded Ensembles: Infinite Width Limit and Operating Regimes
A memory efficient approach to ensembling neural networks is to share mo...
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02/11/2022
Similarity learning for wells based on logging data
One of the first steps during the investigation of geological objects is...
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07/23/2021
A Differentiable Language Model Adversarial Attack on Text Classifiers
Robustness of huge Transformer-based models for natural language process...
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06/15/2021
Adversarial Attacks on Deep Models for Financial Transaction Records
Machine learning models using transaction records as inputs are popular ...
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06/04/2021
Principled change point detection via representation learning
Change points are abrupt alterations in the distribution of sequential d...
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04/03/2021
COHORTNEY: Deep Clustering for Heterogeneous Event Sequences
There is emerging attention towards working with event sequences. In par...
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07/20/2020
Unsupervised anomaly detection for discrete sequence healthcare data
Fraud in healthcare is widespread, as doctors could prescribe unnecessar...
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04/20/2020
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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03/09/2020
Gradient-based adversarial attacks on categorical sequence models via traversing an embedded world
An adversarial attack paradigm explores various scenarios for vulnerabil...
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06/06/2019
Failures detection at directional drilling using real-time analogues search
One of the main challenges in the construction of oil and gas wells is t...
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03/27/2019
Real-time data-driven 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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02/19/2019
Multifidelity Bayesian Optimization for Binomial Output
The key idea of Bayesian optimization is replacing an expensive target f...
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06/08/2018
Data-driven 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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07/12/2017
Large Scale Variable Fidelity Surrogate Modeling
Engineers widely use Gaussian process regression framework to construct ...
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10/21/2016