Pavlos Protopapas

100 papers A* 1A 5B 5Journal 78Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Improving Router Security using BERT. CoRR John Carter, Spiros Mancoridis, Pavlos Protopapas, Brian Mitchell, Benji Lilley
2026	J	`jnl`	Learning embeddings of non-linear PDEs: the Burgers' equation. CoRR Pedro Tarancón-Álvarez, Leonid Sarieddine, Pavlos Protopapas, Raúl Jiménez
2026	J	`jnl`	PTL-PINNs: Perturbation-Guided Transfer Learning with Physics- Informed Neural Networks for Nonlinear Systems. CoRR Duarte Alexandrino, Ben Moseley, Pavlos Protopapas
2025	J	`jnl`	ASTROCO: Self-Supervised Conformer-Style Transformers for Light-Curve Embeddings. CoRR Antony Tan, Pavlos Protopapas, Martina Cádiz-Leyton, Guillermo Cabrera-Vives, Cristobal Donoso-Oliva, Ignacio Becker
2025	J	`jnl`	Applying Vision Transformers on Spectral Analysis of Astronomical Objects. CoRR Luis Felipe Strano Moraes, Ignacio Becker, Pavlos Protopapas, Guillermo Cabrera-Vives
2025	J	`jnl`	Astromer 2. CoRR Cristobal Donoso-Oliva, Ignacio Becker, Pavlos Protopapas, Guillermo Cabrera-Vives, Martina Cádiz-Leyton, Daniel Moreno-Cartagena
2025	J	`jnl`	Efficient PINNs: Multi-Head Unimodular Regularization of the Solutions Space. CoRR Pedro Tarancón-Álvarez, Pablo Tejerina-Pérez, Raúl Jiménez, Pavlos Protopapas
2025	J	`jnl`	Image-Based Multi-Survey Classification of Light Curves with a Pre-Trained Vision Transformer. CoRR Daniel Moreno-Cartagena, Guillermo Cabrera-Vives, Alejandra Muñoz Arancibia, Pavlos Protopapas, Francisco Förster, Márcio Catelán, Amelia Bayo, Pablo A. Estévez, Paula Sánchez-Sáez, Franz E. Bauer, M. Pavez-Herrera, Lorena Hernández-García, Gonzalo Rojas
2025	A	`conf`	Improved Uncertainty Quantification in Physics-Informed Neural Networks Using Error Bounds and Solution Bundles. UAI Pablo Flores, Olga Graf, Pavlos Protopapas, Karim Pichara
2025	J	`jnl`	Improved Uncertainty Quantification in Physics-Informed Neural Networks Using Error Bounds and Solution Bundles. CoRR Pablo Flores, Olga Graf, Pavlos Protopapas, Karim Pichara
2025	J	`jnl`	One-Shot Transfer Learning for Nonlinear PDEs with Perturbative PINNs. CoRR Samuel Auroy, Pavlos Protopapas
2025	J	`jnl`	Recent Advances of NeuroDiffEq - An Open-Source Library for Physics-Informed Neural Networks. CoRR Shuheng Liu, Pavlos Protopapas, David Sondak, Feiyu Chen
2025	J	`jnl`	Stiff Transfer Learning for Physics-Informed Neural Networks. CoRR Emilien Seiler, Wanzhou Lei, Pavlos Protopapas
2025	J	`jnl`	The Denario project: Deep knowledge AI agents for scientific discovery. CoRR Francisco Villaescusa-Navarro, Boris Bolliet, Pablo Villanueva-Domingo, Adrian E. Bayer, Aidan Acquah, Chetana Amancharla, Almog Barzilay-Siegal, Pablo Bermejo, Camille L. Bilodeau, Pablo Cárdenas Ramírez, Miles D. Cranmer, Urbano França, ChangHoon Hahn, Yan-Fei Jiang, Raúl Jiménez, Jun-Young Lee, Antonio Lerario, Osman Mamun, Thomas Meier, Anupam A. Ojha, Pavlos Protopapas, Shimanto Roy, David N. Spergel, Pedro Tarancón-Álvarez, Ujjwal Tiwari, Matteo Viel, Digvijay Wadekar, Chi Wang, Bonny Y. Wang, Licong Xu, Yossi Yovel, Shuwen Yue, Wen-Han Zhou, Qiyao Zhu, Jiajun Zou, Íñigo Zubeldia
2025	—	`conf`	sysBERT: Improved Behavioral Malware Detection using BERT Trained on sys2vec Embeddings. HICSS John Carter, Spiros Mancoridis, Pavlos Protopapas
2024	—	`conf`	Behavioral Malware Detection using a Language Model Classifier Trained on sys2vec Embeddings. HICSS John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin
2024	J	`jnl`	Exact and approximate error bounds for physics-informed neural networks. CoRR Augusto T. Chantada, Pavlos Protopapas, Luca Gomez Bachar, Susana J. Landau, Claudia G. Scóccola
2024	J	`jnl`	Gravitational Duals from Equations of State. CoRR Yago Bea, Raúl Jiménez, David Mateos, Shuheng Liu, Pavlos Protopapas, Pedro Tarancón-Álvarez, Pablo Tejerina-Pérez
2024	—	`conf`	IoT Malware Data Augmentation using a Generative Adversarial Network. HICSS John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin
2024	—	`conf`	contrastBERT: Behavioral Anomaly Detection for Malware Using Contrastive Learning. GameSec (2) John Carter, Spiros Mancoridis, Pavlos Protopapas, Brian Mitchell
2023	J	`jnl`	Generating Images of the M87* Black Hole Using GANs. CoRR Arya Mohan, Pavlos Protopapas, Keerthi Kunnumkai, Cecilia Garraffo, Lindy Blackburn, Koushik Chatterjee, Sheperd S. Doeleman, Razieh Emami, Christian M. Fromm, Yosuke Mizuno, Angelo Ricarte
2023	J	`jnl`	One-Shot Transfer Learning for Nonlinear ODEs. CoRR Wanzhou Lei, Pavlos Protopapas, Joy Parikh
2023	J	`jnl`	Reservoir Computing for Solving Ordinary Differential Equations. Int. J. Artif. Intell. Tools Marios Mattheakis, Hayden Joy, Pavlos Protopapas
2023	A	`conf`	Residual-based error bound for physics-informed neural networks. UAI Shuheng Liu, Xiyue Huang, Pavlos Protopapas
2023	J	`jnl`	Residual-based error bound for physics-informed neural networks. CoRR Shuheng Liu, Xiyue Huang, Pavlos Protopapas
2022	J	`jnl`	ASTROMER: A transformer-based embedding for the representation of light curves. CoRR Cristobal Donoso-Oliva, Ignacio Becker, Pavlos Protopapas, Guillermo Cabrera-Vives, Vishnu M., Harsh Vardhan
2022	J	`jnl`	Con CoRR Manuel Pérez-Carrasco, Pavlos Protopapas, Guillermo Cabrera-Vives
2022	J	`jnl`	DEQGAN: Learning the Loss Function for PINNs with Generative Adversarial Networks. CoRR Blake Bullwinkel, Dylan Randle, Pavlos Protopapas, David Sondak
2022	B	`conf`	Encoding Involutory Invariances in Neural Networks. IJCNN Anwesh Bhattacharya, Marios Mattheakis, Pavlos Protopapas
2022	J	`jnl`	Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks. CoRR Olga Graf, Pablo Flores, Pavlos Protopapas, Karim Pichara
2022	J	`jnl`	Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems. CoRR Shuheng Liu, Xiyue Huang, Pavlos Protopapas
2022	J	`jnl`	Gravitational wave signal recognition and ring-down time estimation via Artificial Neural Networks. Expert Syst. Appl. Gerson R. Santos, Antonio de Pádua Santos, Pavlos Protopapas, Tiago A. E. Ferreira
2022	J	`jnl`	Improving Astronomical Time-series Classification via Data Augmentation with Generative Adversarial Networks. CoRR Germán García-Jara, Pavlos Protopapas, Pablo A. Estévez
2022	J	`jnl`	Improving astroBERT using Semantic Textual Similarity. CoRR Félix Grèzes, 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
2022	B	`conf`	Physics-Informed Neural Networks for Quantum Eigenvalue Problems. IJCNN Henry Jin, Marios Mattheakis, Pavlos Protopapas
2022	J	`jnl`	Physics-Informed Neural Networks for Quantum Eigenvalue Problems. CoRR Henry Jin, Marios Mattheakis, Pavlos Protopapas
2022	J	`jnl`	RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization. CoRR Hayden Joy, Marios Mattheakis, Pavlos Protopapas
2022	J	`jnl`	Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows. CoRR Raphaël Pellegrin, Blake Bullwinkel, Marios Mattheakis, Pavlos Protopapas
2021	J	`jnl`	A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function. CoRR Tiago A. E. Ferreira, Marios Mattheakis, Pavlos Protopapas
2021	J	`jnl`	Adversarial Sampling for Solving Differential Equations with Neural Networks. CoRR Kshitij Parwani, Pavlos Protopapas
2021	J	`jnl`	Building astroBERT, a language model for Astronomy & Astrophysics. CoRR 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
2021	J	`jnl`	Encoding Involutory Invariance in Neural Networks. CoRR Anwesh Bhattacharya, Marios Mattheakis, Pavlos Protopapas
2021	J	`jnl`	Multi-Task Learning based Convolutional Models with Curriculum Learning for the Anisotropic Reynolds Stress Tensor in Turbulent Duct Flow. CoRR Haitz Sáez de Ocáriz Borde, David Sondak, Pavlos Protopapas
2021	J	`jnl`	One-Shot Transfer Learning of Physics-Informed Neural Networks. CoRR Shaan Desai, Marios Mattheakis, Hayden Joy, Pavlos Protopapas, Stephen J. Roberts
2021	J	`jnl`	Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems. CoRR Shaan Desai, Marios Mattheakis, David Sondak, Pavlos Protopapas, Stephen J. Roberts
2021	J	`jnl`	The effect of phased recurrent units in the classification of multiple catalogs of astronomical lightcurves. CoRR Cristobal Donoso-Oliva, Guillermo Cabrera-Vives, Pavlos Protopapas, Rodrigo Carrasco-Davis, Pablo A. Estévez
2021	J	`jnl`	Uncertainty Quantification in Neural Differential Equations. CoRR Olga Graf, Pablo Flores, Pavlos Protopapas, Karim Pichara
2021	J	`jnl`	Unsupervised Reservoir Computing for Solving Ordinary Differential Equations. CoRR Marios Mattheakis, Hayden Joy, Pavlos Protopapas
2020	J	`jnl`	Application of Machine Learning to Predict the Risk of Alzheimer's Disease: An Accurate and Practical Solution for Early Diagnostics. CoRR Courtney Cochrane, David Castineira, Nisreen Shiban, Pavlos Protopapas
2020	—	`conf`	Finding Multiple Solutions of ODEs with Neural Networks. AAAI Spring Symposium: MLPS Marco Di Giovanni, David Sondak, Pavlos Protopapas, Marco Brambilla
2020	—	`conf`	Gender Classification and Bias Mitigation in Facial Images. WebSci Wenying Wu, Panagiotis Michalatos, Pavlos Protopapas, Zheng Yang
2020	J	`jnl`	Gender Classification and Bias Mitigation in Facial Images. CoRR Wenying Wu, Pavlos Protopapas, Zheng Yang, Panagiotis Michalatos
2020	J	`jnl`	Gravitational Wave Detection and Information Extraction via Neural Networks. CoRR Gerson R. Santos, Marcela P. Figueiredo, Antonio de Pádua Santos, Pavlos Protopapas, Tiago A. E. Ferreira
2020	J	`jnl`	Hamiltonian Neural Networks for solving differential equations. CoRR Marios Mattheakis, David Sondak, Akshunna S. Dogra, Pavlos Protopapas
2020	—	`conf`	MPCC: Matching Priors and Conditionals for Clustering. ECCV (23) Nicolás Astorga, Pablo Huijse, Pavlos Protopapas, Pablo A. Estévez
2020	J	`jnl`	MPCC: Matching Priors and Conditionals for Clustering. CoRR Nicolás Astorga, Pablo Huijse, Pavlos Protopapas, Pablo A. Estévez
2020	J	`jnl`	NeuroDiffEq: A Python package for solving differential equations with neural networks. J. Open Source Softw. Feiyu Chen, David Sondak, Pavlos Protopapas, Marios Mattheakis, Shuheng Liu, Devansh Agarwal, Marco Di Giovanni
2020	J	`jnl`	Scalable End-to-end Recurrent Neural Network for Variable star classification. CoRR Ignacio Becker, Karim Pichara, Márcio Catelán, Pavlos Protopapas, Carlos Aguirre, Fatemeh Nikzat
2020	J	`jnl`	Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread. CoRR Alessandro Paticchio, Tommaso Scarlatti, Marios Mattheakis, Pavlos Protopapas, Marco Brambilla
2020	J	`jnl`	Solving Differential Equations Using Neural Network Solution Bundles. CoRR Cedric Flamant, Pavlos Protopapas, David Sondak
2020	J	`jnl`	Unsupervised Learning of Solutions to Differential Equations with Generative Adversarial Networks. CoRR Dylan Randle, Pavlos Protopapas, David Sondak
2020	J	`jnl`	Unsupervised Neural Networks for Quantum Eigenvalue Problems. CoRR Henry Jin, Marios Mattheakis, Pavlos Protopapas
2019	A	`conf`	A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification. SDM Belén Saldías-Fuentes, Pavlos Protopapas, Karim Pichara B.
2019	J	`jnl`	A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification. CoRR Belén Saldías-Fuentes, Pavlos Protopapas, Karim Pichara B.
2019	J	`jnl`	Adversarial Variational Domain Adaptation. CoRR Manuel Pérez-Carrasco, Guillermo Cabrera-Vives, Pavlos Protopapas, Nicolas Astorga, Marouan Belhaj
2019	J	`jnl`	An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves. CoRR Christian Pieringer, Karim Pichara, Márcio Catelán, Pavlos Protopapas
2019	J	`jnl`	An Information Theory Approach on Deciding Spectroscopic Follow Ups. CoRR Javiera Astudillo, Pavlos Protopapas, Karim Pichara, Pablo Huijse
2019	—	`conf`	Big Data Scalability of BayesPhylogenies on Harvard's Ozone 12k Cores. BIOINFORMATICS M. Manjunathaiah, Andrew Meade, R. Thavarajan, Pavlos Protopapas, R. Dave
2019	J	`jnl`	Efficient Optimization of Echo State Networks for Time Series Datasets. CoRR Jacob Reinier Maat, Nikos Gianniotis, Pavlos Protopapas
2019	J	`jnl`	Improving Image Classification Robustness through Selective CNN-Filters Fine-Tuning. CoRR Alessandro Bianchi, Moreno Raimondo Vendra, Pavlos Protopapas, Marco Brambilla
2019	J	`jnl`	Physical Symmetries Embedded in Neural Networks. CoRR Marios Mattheakis, Pavlos Protopapas, David Sondak, Marco Di Giovanni, Efthimios Kaxiras
2019	J	`jnl`	Streaming Classification of Variable Stars. CoRR Lukas Zorich, Karim Pichara, Pavlos Protopapas
2018	J	`jnl`	Deep Variational Transfer: Transfer Learning through Semi-supervised Deep Generative Models. CoRR Marouan Belhaj, Pavlos Protopapas, Weiwei Pan
2018	B	`conf`	Efficient Optimization of Echo State Networks for Time Series Datasets. IJCNN Jacob Reinier Maat, Nikos Gianniotis, Pavlos Protopapas
2018	B	`conf`	Modeling the Effects of Students' Interactions with Immersive Simulations using Markov Switching Systems. EDM Nicholas Hoernle, Ya'akov Gal, Barbara J. Grosz, Pavlos Protopapas, Andee Rubin
2018	J	`jnl`	T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular Sampling. CoRR Giorgia Ramponi, Pavlos Protopapas, Marco Brambilla, Ryan Janssen
2017	J	`jnl`	Robust period estimation using mutual information for multi-band light curves in the synoptic survey era. CoRR Pablo Huijse, Pablo A. Estévez, Francisco Förster, Scott F. Daniel, Andrew J. Connolly, Pavlos Protopapas, Rodrigo Carrasco, José C. Príncipe
2016	J	`jnl`	Clustering Based Feature Learning on Variable Stars. CoRR Cristóbal Mackenzie, Karim Pichara, Pavlos Protopapas
2016	A	`conf`	Cost-Sensitive Batch Mode Active Learning: Designing Astronomical Observation by Optimizing Telescope Time and Telescope Choice. SDM Xide Xia, Pavlos Protopapas, Finale Doshi-Velez
2016	A*	`conf`	Optimizing the Multiclass F-Measure via Biconcave Programming. ICDM Harikrishna Narasimhan, Weiwei Pan, Purushottam Kar, Pavlos Protopapas, Harish G. Ramaswamy
2015	J	`jnl`	Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases. CoRR Pablo Huijse, Pablo A. Estévez, Pavlos Protopapas, José C. Príncipe, Pablo Zegers
2014	J	`jnl`	A Novel, Fully Automated Pipeline for Period Estimation in the EROS 2 Data Set. CoRR Pavlos Protopapas, Pablo Huijse, Pablo A. Estévez, Pablo Zegers, José C. Príncipe
2014	J	`jnl`	Computational Intelligence Challenges and Applications on Large-Scale Astronomical Time Series Databases. IEEE Comput. Intell. Mag. Pablo Huijse, Pablo A. Estévez, Pavlos Protopapas, José C. Príncipe, Pablo Zegers
2014	J	`jnl`	Supervised detection of anomalous light-curves in massive astronomical catalogs. CoRR Isadora nun, Karim Pichara, Pavlos Protopapas, Dae-Won Kim
2013	J	`jnl`	Automatic Classification of Variable Stars in Catalogs with missing data. CoRR Karim Pichara, Pavlos Protopapas
2012	J	`jnl`	An Information Theoretic Algorithm for Finding Periodicities in Stellar Light Curves CoRR Pablo Huijse, Pablo A. Estévez, Pavlos Protopapas, Pablo Zegers, José C. Príncipe
2012	J	`jnl`	An Information Theoretic Algorithm for Finding Periodicities in Stellar Light Curves. IEEE Trans. Signal Process. Pablo Huijse, Pablo A. Estévez, Pavlos Protopapas, Pablo Zegers, José Carlos Príncipe
2012	J	`jnl`	Infinite Shift-invariant Grouped Multi-task Learning for Gaussian Processes CoRR Yuyang Wang, Roni Khardon, Pavlos Protopapas
2011	—	`conf`	Estimation of periodicity in non-uniformly sampled astronomical data using a 2D kernel in correntropy. MLSP Bibhu Prasad Mishra, José C. Príncipe, Pablo A. Estévez, Pavlos Protopapas
2011	J	`jnl`	Nonparametric Bayesian Estimation of Periodic Functions CoRR Yuyang Wang, Roni Khardon, Pavlos Protopapas
2011	J	`jnl`	Period Estimation in Astronomical Time Series Using Slotted Correntropy CoRR Pablo Huijse, Pablo A. Estévez, Pablo Zegers, José Carlos Príncipe, Pavlos Protopapas
2011	J	`jnl`	Period Estimation in Astronomical Time Series Using Slotted Correntropy. IEEE Signal Process. Lett. Pablo Huijse, Pablo A. Estévez, Pablo Zegers, José Carlos Príncipe, Pavlos Protopapas
2010	B	`conf`	Period detection in light curves from astronomical objects using correntropy. IJCNN Pablo A. Estévez, Pablo Huijse, Pablo Zegers, José C. Príncipe, Pavlos Protopapas
2010	—	`conf`	Shift-Invariant Grouped Multi-task Learning for Gaussian Processes. ECML/PKDD (3) Yuyang Wang, Roni Khardon, Pavlos Protopapas
2009	J	`jnl`	Discovering arbitrary event types in time series. Stat. Anal. Data Min. Dan Preston, Pavlos Protopapas, Carla E. Brodley
2009	A	`conf`	Event Discovery in Time Series. SDM Dan Preston, Pavlos Protopapas, Carla E. Brodley
2009	J	`jnl`	Finding Anomalous Periodic Time Series: An Application to Catalogs of Periodic Variable Stars CoRR Umaa Rebbapragada, Pavlos Protopapas, Carla E. Brodley, Charles R. Alcock
2009	J	`jnl`	Finding anomalous periodic time series. Mach. Learn. Umaa Rebbapragada, Pavlos Protopapas, Carla E. Brodley, Charles R. Alcock
2009	—	`conf`	Kernels for Periodic Time Series Arising in Astronomy. ECML/PKDD (2) Gabriel Wachman, Roni Khardon, Pavlos Protopapas, Charles R. Alcock
2009	J	`jnl`	Supporting exact indexing of arbitrarily rotated shapes and periodic time series under Euclidean and warping distance measures. VLDB J. Eamonn J. Keogh, Li Wei, Xiaopeng Xi, Michail Vlachos, Sang-Hee Lee, Pavlos Protopapas