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02/08/2022
Contrastive predictive coding for Anomaly Detection in Multi-variate Time Series Data
Anomaly detection in multi-variate time series (MVTS) data is a huge cha...
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01/24/2022
PaRT: Parallel Learning Towards Robust and Transparent AI
This paper takes a parallel learning approach for robust and transparent...
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01/07/2022
Incremental Knowledge Tracing from Multiple Schools
Knowledge tracing is the task of predicting a learner's future performan...
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09/23/2021
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series
Several techniques for multivariate time series anomaly detection have b...
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12/12/2020
Knowledge Capture and Replay for Continual Learning
Deep neural networks have shown promise in several domains, and the lear...
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11/18/2019
Bayesian Recurrent Framework for Missing Data Imputation and Prediction with Clinical Time Series
Real-world clinical time series data sets exhibit a high prevalence of m...
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03/21/2019
Efficient single input-output layer spiking neural classifier with time-varying weight model
This paper presents a supervised learning algorithm, namely, the Synapti...
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03/08/2019
Fast Prototyping a Dialogue Comprehension System for Nurse-Patient Conversations on Symptom Monitoring
Data for human-human spoken dialogues for research and development are c...
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02/28/2019
A novel method for extracting interpretable knowledge from a spiking neural classifier with time-varying synaptic weights
This paper presents a novel method for information interpretability in a...
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11/15/2018
Predicting thermoelectric properties from crystal graphs and material descriptors - first application for functional materials
We introduce the use of Crystal Graph Convolutional Neural Networks (CGC...
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09/24/2018
Autonomous Deep Learning: Incremental Learning of Denoising Autoencoder for Evolving Data Streams
The generative learning phase of Autoencoder (AE) and its successor Deno...
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03/06/2018
