Pavlos Protopapas

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 62

Top Topics

Transfer Learning

Differential Equations

Dynamical Systems

Top Venues

Publications

John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin
IoT Malware Data Augmentation using a Generative Adversarial Network. HICSS (2024)
Yago Bea, Raúl Jiménez, David Mateos, Shuheng Liu, Pavlos Protopapas, Pedro Tarancón-Álvarez, Pablo Tejerina-Pérez
Gravitational Duals from Equations of State. CoRR (2024)
John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin
Behavioral Malware Detection using a Language Model Classifier Trained on sys2vec Embeddings. HICSS (2024)
Marios Mattheakis, Hayden Joy, Pavlos Protopapas
Reservoir Computing for Solving Ordinary Differential Equations. Int. J. Artif. Intell. Tools 32 (1) (2023)
Shuheng Liu, Xiyue Huang, Pavlos Protopapas
Residual-based error bound for physics-informed neural networks. CoRR (2023)
Shuheng Liu, Xiyue Huang, Pavlos Protopapas
Residual-based error bound for physics-informed neural networks. UAI (2023)
Wanzhou Lei, Pavlos Protopapas, Joy Parikh
One-Shot Transfer Learning for Nonlinear ODEs. CoRR (2023)
Arya Mohan, Pavlos Protopapas, Keerthi Kunnumkai, Cecilia Garraffo, Lindy Blackburn, Koushik Chatterjee, Sheperd S. Doeleman, Razieh Emami, Christian M. Fromm, Yosuke Mizuno, Angelo Ricarte
Generating Images of the M87* Black Hole Using GANs. CoRR (2023)
C. Donoso-Oliva, I. Becker, Pavlos Protopapas, Guillermo Cabrera-Vives, Vishnu M., Harsh Vardhan
ASTROMER: A transformer-based embedding for the representation of light curves. CoRR (2022)
Gerson R. Santos, Antonio de Pádua Santos, Pavlos Protopapas, Tiago A. E. Ferreira
Gravitational wave signal recognition and ring-down time estimation via Artificial Neural Networks. Expert Syst. Appl. 207 (2022)
Shuheng Liu, Xiyue Huang, Pavlos Protopapas
Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems. CoRR (2022)
Manuel Pérez-Carrasco, Pavlos Protopapas, Guillermo Cabrera-Vives
DA: Simplifying Semi-supervised Domain Adaptation by Learning Consistent and Contrastive Feature Representations. CoRR (2022)
Anwesh Bhattacharya, Marios Mattheakis, Pavlos Protopapas
Encoding Involutory Invariances in Neural Networks. IJCNN (2022)
Henry Jin, Marios Mattheakis, Pavlos Protopapas
Physics-Informed Neural Networks for Quantum Eigenvalue Problems. IJCNN (2022)
Blake Bullwinkel, Dylan Randle, Pavlos Protopapas, David Sondak
DEQGAN: Learning the Loss Function for PINNs with Generative Adversarial Networks. CoRR (2022)
Hayden Joy, Marios Mattheakis, Pavlos Protopapas
RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization. CoRR (2022)
Felix Grezes, Thomas Allen, Sergi Blanco-Cuaresma, Alberto Accomazzi, Michael J. Kurtz, Golnaz Shapurian, Edwin A. Henneken, Carolyn S. Grant, Donna M. Thompson, Timothy W. Hostetler, Matthew R. Templeton, Kelly E. Lockhart, Shinyi Chen, Jennifer Koch, Taylor Jacovich, Pavlos Protopapas
Improving astroBERT using Semantic Textual Similarity. CoRR (2022)
Raphaël Pellegrin, Blake Bullwinkel, Marios Mattheakis, Pavlos Protopapas
Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows. CoRR (2022)
Henry Jin, Marios Mattheakis, Pavlos Protopapas
Physics-Informed Neural Networks for Quantum Eigenvalue Problems. CoRR (2022)
Germán García-Jara, Pavlos Protopapas, Pablo A. Estévez
Improving Astronomical Time-series Classification via Data Augmentation with Generative Adversarial Networks. CoRR (2022)
Olga Graf, Pablo Flores, Pavlos Protopapas, Karim Pichara
Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks. CoRR (2022)
C. Donoso-Oliva, Guillermo Cabrera-Vives, Pavlos Protopapas, Rodrigo Carrasco-Davis, Pablo A. Estévez
The effect of phased recurrent units in the classification of multiple catalogs of astronomical lightcurves. CoRR (2021)
Félix Grèzes, Sergi Blanco-Cuaresma, Alberto Accomazzi, Michael J. Kurtz, Golnaz Shapurian, Edwin A. Henneken, Carolyn S. Grant, Donna M. Thompson, Roman Chyla, Stephen McDonald, Timothy W. Hostetler, Matthew R. Templeton, Kelly E. Lockhart, Nemanja Martinovic, Shinyi Chen, Chris Tanner, Pavlos Protopapas
Building astroBERT, a language model for Astronomy & Astrophysics. CoRR (2021)
Shaan Desai, Marios Mattheakis, David Sondak, Pavlos Protopapas, Stephen J. Roberts
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems. CoRR (2021)
Tiago A. E. Ferreira, Marios Mattheakis, Pavlos Protopapas
A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function. CoRR (2021)
Anwesh Bhattacharya, Marios Mattheakis, Pavlos Protopapas
Encoding Involutory Invariance in Neural Networks. CoRR (2021)
Marios Mattheakis, Hayden Joy, Pavlos Protopapas
Unsupervised Reservoir Computing for Solving Ordinary Differential Equations. CoRR (2021)
Kshitij Parwani, Pavlos Protopapas
Adversarial Sampling for Solving Differential Equations with Neural Networks. CoRR (2021)
Haitz Sáez de Ocáriz Borde, David Sondak, Pavlos Protopapas
Multi-Task Learning based Convolutional Models with Curriculum Learning for the Anisotropic Reynolds Stress Tensor in Turbulent Duct Flow. CoRR (2021)
Shaan Desai, Marios Mattheakis, Hayden Joy, Pavlos Protopapas, Stephen J. Roberts
One-Shot Transfer Learning of Physics-Informed Neural Networks. CoRR (2021)
Olga Graf, Pablo Flores, Pavlos Protopapas, Karim Pichara
Uncertainty Quantification in Neural Differential Equations. CoRR (2021)
Wenying Wu, Panagiotis Michalatos, Pavlos Protopapas, Zheng Yang
Gender Classification and Bias Mitigation in Facial Images. WebSci (2020)
Henry Jin, Marios Mattheakis, Pavlos Protopapas
Unsupervised Neural Networks for Quantum Eigenvalue Problems. CoRR (2020)
Nicolás Astorga, Pablo Huijse, Pavlos Protopapas, Pablo A. Estévez
MPCC: Matching Priors and Conditionals for Clustering. ECCV (23) (2020)
Marco Di Giovanni, David Sondak, Pavlos Protopapas, Marco Brambilla
Finding Multiple Solutions of ODEs with Neural Networks. AAAI Spring Symposium: MLPS (2020)
Wenying Wu, Pavlos Protopapas, Zheng Yang, Panagiotis Michalatos
Gender Classification and Bias Mitigation in Facial Images. CoRR (2020)
Ignacio Becker, Karim Pichara, Márcio Catelán, Pavlos Protopapas, Carlos Aguirre, Fatemeh Nikzat
Scalable End-to-end Recurrent Neural Network for Variable star classification. CoRR (2020)
Nicolás Astorga, Pablo Huijse, Pavlos Protopapas, Pablo A. Estévez
MPCC: Matching Priors and Conditionals for Clustering. CoRR (2020)
Courtney Cochrane, David Castineira, Nisreen Shiban, Pavlos Protopapas
Application of Machine Learning to Predict the Risk of Alzheimer's Disease: An Accurate and Practical Solution for Early Diagnostics. CoRR (2020)
Dylan Randle, Pavlos Protopapas, David Sondak
Unsupervised Learning of Solutions to Differential Equations with Generative Adversarial Networks. CoRR (2020)
Alessandro Paticchio, Tommaso Scarlatti, Marios Mattheakis, Pavlos Protopapas, Marco Brambilla
Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread. CoRR (2020)
Cedric Flamant, Pavlos Protopapas, David Sondak
Solving Differential Equations Using Neural Network Solution Bundles. CoRR (2020)
Feiyu Chen, David Sondak, Pavlos Protopapas, Marios Mattheakis, Shuheng Liu, Devansh Agarwal, Marco Di Giovanni
NeuroDiffEq: A Python package for solving differential equations with neural networks. J. Open Source Softw. 5 (46) (2020)
Gerson R. Santos, Marcela P. Figueiredo, Antonio de Pádua Santos, Pavlos Protopapas, Tiago A. E. Ferreira
Gravitational Wave Detection and Information Extraction via Neural Networks. CoRR (2020)
Marios Mattheakis, David Sondak, Akshunna S. Dogra, Pavlos Protopapas
Hamiltonian Neural Networks for solving differential equations. CoRR (2020)
Manuel Pérez-Carrasco, Guillermo Cabrera-Vives, Pavlos Protopapas, Nicolas Astorga, Marouan Belhaj
Adversarial Variational Domain Adaptation. CoRR (2019)
Alessandro Bianchi, Moreno Raimondo Vendra, Pavlos Protopapas, Marco Brambilla
Improving Image Classification Robustness through Selective CNN-Filters Fine-Tuning. CoRR (2019)
Belén Saldías-Fuentes, Pavlos Protopapas, Karim Pichara B.
A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification. SDM (2019)
Jacob Reinier Maat, Nikos Gianniotis, Pavlos Protopapas
Efficient Optimization of Echo State Networks for Time Series Datasets. CoRR (2019)
Lukas Zorich, Karim Pichara, Pavlos Protopapas
Streaming Classification of Variable Stars. CoRR (2019)
Javiera Astudillo, Pavlos Protopapas, Karim Pichara, Pablo Huijse
An Information Theory Approach on Deciding Spectroscopic Follow Ups. CoRR (2019)
Marios Mattheakis, Pavlos Protopapas, David Sondak, Marco Di Giovanni, Efthimios Kaxiras
Physical Symmetries Embedded in Neural Networks. CoRR (2019)
Belén Saldías-Fuentes, Pavlos Protopapas, Karim Pichara B.
A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification. CoRR (2019)
Christian Pieringer, Karim Pichara, Márcio Catelán, Pavlos Protopapas
An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves. CoRR (2019)
Giorgia Ramponi, Pavlos Protopapas, Marco Brambilla, Ryan Janssen
T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling. CoRR (2018)
Jacob Reinier Maat, Nikos Gianniotis, Pavlos Protopapas
Efficient Optimization of Echo State Networks for Time Series Datasets. IJCNN (2018)
Marouan Belhaj, Pavlos Protopapas, Weiwei Pan
Deep Variational Transfer: Transfer Learning through Semi-supervised Deep Generative Models. CoRR (2018)
Nicholas Hoernle, Ya'akov Gal, Barbara J. Grosz, Pavlos Protopapas, Andee Rubin
Modeling the Effects of Students' Interactions with Immersive Simulations using Markov Switching Systems. EDM (2018)
Pablo Huijse, Pablo A. Estévez, Francisco Förster, Scott F. Daniel, Andrew J. Connolly, Pavlos Protopapas, Rodrigo Carrasco, José C. Príncipe
Robust period estimation using mutual information for multi-band light curves in the synoptic survey era. CoRR (2017)
Cristóbal Mackenzie, Karim Pichara, Pavlos Protopapas
Clustering Based Feature Learning on Variable Stars. CoRR (2016)
Xide Xia, Pavlos Protopapas, Finale Doshi-Velez
Cost-Sensitive Batch Mode Active Learning: Designing Astronomical Observation by Optimizing Telescope Time and Telescope Choice. SDM (2016)
Harikrishna Narasimhan, Weiwei Pan, Purushottam Kar, Pavlos Protopapas, Harish G. Ramaswamy
Optimizing the Multiclass F-Measure via Biconcave Programming. ICDM (2016)
Pablo Huijse, Pablo A. Estévez, Pavlos Protopapas, José C. Príncipe, Pablo Zegers
Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases. CoRR (2015)
Pavlos Protopapas, Pablo Huijse, Pablo A. Estévez, Pablo Zegers, José C. Príncipe
A Novel, Fully Automated Pipeline for Period Estimation in the EROS 2 Data Set. CoRR (2014)
Isadora nun, Karim Pichara, Pavlos Protopapas, Dae-Won Kim
Supervised detection of anomalous light-curves in massive astronomical catalogs. CoRR (2014)
Pablo Huijse, Pablo A. Estévez, Pavlos Protopapas, José C. Príncipe, Pablo Zegers
Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases. IEEE Comput. Intell. Mag. 9 (3) (2014)
Karim Pichara, Pavlos Protopapas
Automatic Classification of Variable Stars in Catalogs with missing data. CoRR (2013)
Pablo Huijse, Pablo A. Estévez, Pavlos Protopapas, Pablo Zegers, José C. Príncipe
An Information Theoretic Algorithm for Finding Periodicities in Stellar Light Curves CoRR (2012)
Pablo Huijse, Pablo A. Estévez, Pavlos Protopapas, Pablo Zegers, José Carlos Príncipe
An Information Theoretic Algorithm for Finding Periodicities in Stellar Light Curves. IEEE Trans. Signal Process. 60 (10) (2012)
Yuyang Wang, Roni Khardon, Pavlos Protopapas
Infinite Shift-invariant Grouped Multi-task Learning for Gaussian Processes CoRR (2012)
Bibhu Prasad Mishra, José C. Príncipe, Pablo A. Estévez, Pavlos Protopapas
Estimation of periodicity in non-uniformly sampled astronomical data using a 2D kernel in correntropy. MLSP (2011)
Yuyang Wang, Roni Khardon, Pavlos Protopapas
Nonparametric Bayesian Estimation of Periodic Functions CoRR (2011)
Pablo Huijse, Pablo A. Estévez, Pablo Zegers, José Carlos Príncipe, Pavlos Protopapas
Period Estimation in Astronomical Time Series Using Slotted Correntropy. IEEE Signal Process. Lett. 18 (6) (2011)
Pablo Huijse, Pablo A. Estévez, Pablo Zegers, José Carlos Príncipe, Pavlos Protopapas
Period Estimation in Astronomical Time Series Using Slotted Correntropy CoRR (2011)
Pablo A. Estévez, Pablo Huijse, Pablo Zegers, José C. Príncipe, Pavlos Protopapas
Period detection in light curves from astronomical objects using correntropy. IJCNN (2010)
Yuyang Wang, Roni Khardon, Pavlos Protopapas
Shift-Invariant Grouped Multi-task Learning for Gaussian Processes. ECML/PKDD (3) (2010)
Eamonn J. Keogh, Li Wei, Xiaopeng Xi, Michail Vlachos, Sang-Hee Lee, Pavlos Protopapas
Supporting exact indexing of arbitrarily rotated shapes and periodic time series under Euclidean and warping distance measures. VLDB J. 18 (3) (2009)
Gabriel Wachman, Roni Khardon, Pavlos Protopapas, Charles R. Alcock
Kernels for Periodic Time Series Arising in Astronomy. ECML/PKDD (2) (2009)
Umaa Rebbapragada, Pavlos Protopapas, Carla E. Brodley, Charles R. Alcock
Finding Anomalous Periodic Time Series: An Application to Catalogs of Periodic Variable Stars CoRR (2009)
Dan Preston, Pavlos Protopapas, Carla E. Brodley
Event Discovery in Time Series. SDM (2009)
Dan Preston, Pavlos Protopapas, Carla E. Brodley
Discovering arbitrary event types in time series. Stat. Anal. Data Min. 2 (5-6) (2009)
Umaa Rebbapragada, Pavlos Protopapas, Carla E. Brodley, Charles R. Alcock
Finding anomalous periodic time series. Mach. Learn. 74 (3) (2009)