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06/29/2023
Obeying the Order: Introducing Ordered Transfer Hyperparameter Optimisation
We introduce ordered transfer hyperparameter optimisation (OTHPO), a ver...
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03/21/2022
Diverse Counterfactual Explanations for Anomaly Detection in Time Series
Data-driven methods that detect anomalies in times series data are ubiqu...
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02/23/2022
Multivariate Quantile Function Forecaster
We propose Multivariate Quantile Function Forecaster (MQF^2), a global p...
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01/18/2022
Online Time Series Anomaly Detection with State Space Gaussian Processes
We propose r-ssGPFA, an unsupervised online anomaly detection model for ...
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12/29/2021
Monte Carlo EM for Deep Time Series Anomaly Detection
Time series data are often corrupted by outliers or other kinds of anoma...
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11/12/2021
Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting
Quantile regression is an effective technique to quantify uncertainty, f...
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09/10/2021
A Study of Joint Graph Inference and Forecasting
We study a recent class of models which uses graph neural networks (GNNs...
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07/16/2021
Neural Contextual Anomaly Detection for Time Series
We introduce Neural Contextual Anomaly Detection (NCAD), a framework for...
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06/21/2021
Spliced Binned-Pareto Distribution for Robust Modeling of Heavy-tailed Time Series
This work proposes a novel method to robustly and accurately model time ...
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06/24/2019
EQuANt (Enhanced Question Answer Network)
Machine Reading Comprehension (MRC) is an important topic in the domain ...
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01/25/2019
