Pavlos Protopapas
Orcid: 0000-0002-8178-8463
According to our database1,
Pavlos Protopapas
authored at least 74 papers
between 2009 and 2024.
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Bibliography
2024
Behavioral Malware Detection using a Language Model Classifier Trained on sys2vec Embeddings.
Proceedings of the 57th Hawaii International Conference on System Sciences, 2024
Proceedings of the 57th Hawaii International Conference on System Sciences, 2024
2023
Int. J. Artif. Intell. Tools, February, 2023
Proceedings of the Uncertainty in Artificial Intelligence, 2023
2022
Gravitational wave signal recognition and ring-down time estimation via Artificial Neural Networks.
Expert Syst. Appl., 2022
Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks.
CoRR, 2022
Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows.
CoRR, 2022
CoRR, 2022
RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization.
CoRR, 2022
Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems.
CoRR, 2022
Improving Astronomical Time-series Classification via Data Augmentation with Generative Adversarial Networks.
CoRR, 2022
CoRR, 2022
Con<sup>2</sup>DA: Simplifying Semi-supervised Domain Adaptation by Learning Consistent and Contrastive Feature Representations.
CoRR, 2022
Proceedings of the International Joint Conference on Neural Networks, 2022
Proceedings of the International Joint Conference on Neural Networks, 2022
2021
CoRR, 2021
Multi-Task Learning based Convolutional Models with Curriculum Learning for the Anisotropic Reynolds Stress Tensor in Turbulent Duct Flow.
CoRR, 2021
CoRR, 2021
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems.
CoRR, 2021
The effect of phased recurrent units in the classification of multiple catalogs of astronomical lightcurves.
CoRR, 2021
A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function.
CoRR, 2021
2020
NeuroDiffEq: A Python package for solving differential equations with neural networks.
J. Open Source Softw., 2020
Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread.
CoRR, 2020
Unsupervised Learning of Solutions to Differential Equations with Generative Adversarial Networks.
CoRR, 2020
Application of Machine Learning to Predict the Risk of Alzheimer's Disease: An Accurate and Practical Solution for Early Diagnostics.
CoRR, 2020
CoRR, 2020
CoRR, 2020
Proceedings of the WebSci '20: 12th ACM Conference on Web Science, 2020
Proceedings of the Computer Vision - ECCV 2020, 2020
Proceedings of the AAAI 2020 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 23rd - to, 2020
2019
CoRR, 2019
An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves.
CoRR, 2019
A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019
Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2019), 2019
2018
Deep Variational Transfer: Transfer Learning through Semi-supervised Deep Generative Models.
CoRR, 2018
T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling.
CoRR, 2018
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018
Modeling the Effects of Students' Interactions with Immersive Simulations using Markov Switching Systems.
Proceedings of the 11th International Conference on Educational Data Mining, 2018
2017
Robust period estimation using mutual information for multi-band light curves in the synoptic survey era.
CoRR, 2017
2016
Cost-Sensitive Batch Mode Active Learning: Designing Astronomical Observation by Optimizing Telescope Time and Telescope Choice.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016
Proceedings of the IEEE 16th International Conference on Data Mining, 2016
2014
CoRR, 2014
CoRR, 2014
Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases.
IEEE Comput. Intell. Mag., 2014
2013
2012
An Information Theoretic Algorithm for Finding Periodicities in Stellar Light Curves.
IEEE Trans. Signal Process., 2012
CoRR, 2012
2011
IEEE Signal Process. Lett., 2011
Estimation of periodicity in non-uniformly sampled astronomical data using a 2D kernel in correntropy.
Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011
2010
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010
Proceedings of the International Joint Conference on Neural Networks, 2010
2009
Supporting exact indexing of arbitrarily rotated shapes and periodic time series under Euclidean and warping distance measures.
VLDB J., 2009
Finding Anomalous Periodic Time Series: An Application to Catalogs of Periodic Variable Stars
CoRR, 2009
Proceedings of the SIAM International Conference on Data Mining, 2009
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009