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Expand Up @@ -52,6 +52,153 @@ <h1 class="display-4">Publications</h1>
<div class="row">
<div class="col-sm">
<ul class="list-pointer list-pointer-sm list-pointer-primary">
<li>Bea, Y., Jiménez, R., Mateos, D., Liu, S., Protopapas, P., Tarancón-Álvarez, P., Tejerina-Pérez, P.
"Gravitational duals from equations of state." Journal of High Energy Physics, 2024(7), 87 (2024).</li>

<li>John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin.
"IoT Malware Data Augmentation using a Generative Adversarial Network." HICSS 2024: 7572-7581 (2024).</li>

<li>John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin.
"Behavioral Malware Detection using a Language Model Classifier Trained on sys2vec Embeddings."
HICSS 2024: 7582-7591 (2024).</li>

<li>A.T. Chantada, S.J. Landau, P. Protopapas, C.G. Scóccola, C. Garraffo.
"Faster Bayesian inference with neural network bundles and new results for ΛCDM models."
Physical Review D 109 (12), 123514 (2024).</li>

<li>V.S. Pérez Díaz, J. Ingram, V. Kashyap, J. Martinez Galarza, P. Protopapas.
"Enhancing Chandra-Gaia Crossmatching with Machine Learning."
AAS/High Energy Astrophysics Division 21, 105.02 (2024).</li>

<li>A. Mohan, P. Protopapas, K. Kunnumkai, C. Garraffo, L. Blackburn, et al.
"Generating images of the M87* black hole using GANs." Monthly Notices of the Royal Astronomical Society 527 (4),
10965-10974 (2024).</li>

<li>M. Cresitello-Dittmar, J. McDowell, D. Tody, T. Budavari, M. Dolensky, et al.
"IVOA Spectrum Data Model Version 1.2." IVOA Recommendation 15 December 2023.</li>

<li>A.T. Chantada, S.J. Landau, P. Protopapas, C.G. Scóccola, C. Garraffo.
"NN bundle method applied to cosmology: an improvement in computational times."
arXiv preprint arXiv:2311.15955 (2023).</li>

<li>W. Lei, P. Protopapas, J. Parikh. "One-Shot Transfer Learning for Nonlinear ODEs."
arXiv preprint arXiv:2311.14931 (2023).</li>

<li>D. Moreno-Cartagena, G. Cabrera-Vives, P. Protopapas, C. Donoso-Oliva, et al.
"Positional Encodings for Light Curve Transformers: Playing with Positions and Attention."
arXiv preprint arXiv:2308.06404 (2023).</li>

<li>K. Ly, J. Kurlander, M. Holman, M. Payne, A. Heinze, P. Bernardinelli, et al. "2010 RJ226." Minor Planet Electronic Circulars 2023.</li>

<li>J. Carter, S. Mancoridis, P. Protopapas. "Optimal data sample length for system call traces for malware detection in an iot ecosystem." 2023 3rd International Conference on Electrical, Computer, Communications and Electronics Engineering.</li>

<li>S. Liu, X. Huang, P. Protopapas. "Residual-based error bound for physics-informed neural networks." Uncertainty in Artificial Intelligence, 1284-1293 (2023).</li>

<li>A.T. Chantada, S.J. Landau, P. Protopapas, C.G. Scóccola, C. Garraffo. "Cosmology-informed neural networks to solve the background dynamics of the Universe." Physical Review D 107 (6), 063523 (2023).</li>

<li>M. Mattheakis, H. Joy, P. Protopapas. "Reservoir Computing for Solving Ordinary Differential Equations." International Journal on Artificial Intelligence Tools 32 (01), 2350030 (2023).</li>

<li>J. Astudillo, P. Protopapas, K. Pichara, I. Becker. "A Reinforcement Learning–Based Follow-up Framework." The Astronomical Journal 165 (3), 118 (2023).</li>

<li>C. Donoso-Oliva, I. Becker, P. Protopapas, G. Cabrera-Vives, M. Vishnu, et al. "ASTROMER-A transformer-based embedding for the representation of light curves." Astronomy & Astrophysics 670, A54 (2023).</li>

<li>T. Allen, F. Grezes, G. Shapurian, S. Blanco-Cuaresma, C. Grant, et al. "ADS Machine Learning and Deep Learning Efforts." American Astronomical Society Meeting Abstracts 55 (2), 177.37 (2023).</li>

<li>T.A.E. Ferreira, M. Mattheakis, P. Protopapas. "A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function." arXiv:2101.06100 (2021).</li>

<li>D. Sondak, P. Protopapas. "Learning a Reduced Basis of Dynamical Systems using an Autoencoder." arXiv:2011.07346 (2020).</li>

<li>R. Fang, D. Sondak, P. Protopapas, S. Succi. "Neural network models for the anisotropic Reynolds stress tensor in turbulent channel flow." Journal of Turbulence 21(9-10), 525-543 (2020).</li>

<li>L. Zorich, K. Pichara, P. Protopapas. "Streaming classification of variable stars." Monthly Notices of the Royal Astronomical Society 492(2), 2897-2909 (2020).</li>

<li>C. Flamant, P. Protopapas, D. Sondak. "Solving Differential Equations Using Neural Network Solution Bundles." arXiv preprint arXiv:2006.14372 (2020).</li>

<li>F. Chen, D. Sondak, P. Protopapas, M. Mattheakis, S. Liu, D. Agarwal, M. Di Giovanni. "NeuroDiffEq: A Python package for solving differential equations with neural networks." Journal of Open Source Software 5(46), 1931 (2020).</li>

<li>N. Astorga, P. Huijse, P. Protopapas, P. Estévez. "Matching Priors and Conditionals for Clustering." European Conference on Computer Vision, 658-677 (2020).</li>

<li>W. Wu, P. Protopapas, Z. Yang, P. Michalatos. "Gender classification and bias mitigation in facial images." 12th ACM Conference on Web Science, 106-114 (2020).</li>

<li>H. Jin, M. Mattheakis, P. Protopapas. "Unsupervised Neural Networks for Quantum Eigenvalue Problems." arXiv:2010.05075 (2020).</li>

<li>M. Mattheakis, D. Sondak, A.S. Dogra, P. Protopapas. "Hamiltonian Neural Networks for solving differential equations." arXiv:2001.11107 (2020).</li>

<li>A. Paticchio, T. Scarlatti, M. Mattheakis, P. Protopapas, M. Brambilla. "Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread." arXiv e-prints: 2020arXiv201005074P (2020).</li>

<li>D. Randle, P. Protopapas, D. Sondak. "Unsupervised Learning of Solutions to Differential Equations with Generative Adversarial Networks." arXiv preprint arXiv:2007.11133 (2020).</li>

<li>R. Carrasco-Davis, G. Cabrera-Vives, F. Förster, P.A. Estevez, P. Huijse, P. Protopapas, I. Reyes, J. Martínez-Palomera, C. Donoso. "Deep learning for image sequence classification of astronomical events." Publications of the Astronomical Society of the Pacific 131(1004), 108006 (2019).</li>

<li>M. Mattheakis, P. Protopapas, D. Sondak, M. Di Giovanni, E. Kaxiras. "Physical symmetries embedded in neural networks." arXiv preprint arXiv:1904.08991 (2019).</li>

<li>M. Pérez-Carrasco, G. Cabrera-Vives, M. Martinez-Marin, P. Cerulo, R. Demarco, P. Protopapas, J. Godoy. "Multiband galaxy morphologies for CLASH: a convolutional neural network transferred from CANDELS." Publications of the Astronomical Society of the Pacific 131(1004), 108002 (2019).</li>

<li>C. Pieringer, K. Pichara, M. Catelán, P. Protopapas. "An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves." Monthly Notices of the Royal Astronomical Society 484(3), 3071-3077 (2019).</li>

<li>J. Astudillo, P. Protopapas, K. Pichara, P. Huijse. "An Information Theory Approach on Deciding Spectroscopic Follow-ups." The Astronomical Journal 159(1), 16 (2019).</li>

<li>A. Bianchi, M.R. Vendra, P. Protopapas, M. Brambilla. "Improving image classification robustness through selective CNN-filters fine-tuning." arXiv preprint arXiv:1904.03949 (2019).</li>

<li>B. Saldias-Fuentes, P. Protopapas. "A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification." Proceedings of the 2019 SIAM International Conference on Data Mining, 756-764 (2019).</li>

<li>M.J. Holman, M.J. Payne, W. Fraser, P. Lacerda, M.T. Bannister, M. Lackner, Y.T. Chen, H.W. Lin, K.W. Smith, R. Kokotanekova, D. Young. "A dwarf planet class object in the 21:5 resonance with Neptune." The Astrophysical Journal Letters 855(1), L6 (2018).</li>

<li>G. Ramponi, P. Protopapas, M. Brambilla, R. Janssen. "T-cgan: Conditional generative adversarial network for data augmentation in noisy time series with irregular sampling." arXiv preprint arXiv:1811.08295 (2018).</li>

<li>J. Martínez-Palomera, F. Förster, P. Protopapas, J.C. Maureira, P. Lira, G. Cabrera-Vives, P. Huijse, L. Galbany, T. De Jaeger, S. González-Gaitán, G. Medina. "The High Cadence Transit Survey (HiTS): Compilation and Characterization of Light-curve Catalogs." The Astronomical Journal 156(5), 186 (2018).</li>

<li>P. Huijse, P.A. Estévez, F. Förster, S.F. Daniel, A.J. Connolly, P. Protopapas, R. Carrasco, J.C. Príncipe. "Robust Period Estimation Using Mutual Information for Multiband Light Curves in the Synoptic Survey Era." The Astrophysical Journal Supplement Series 236(1), 12 (2018).</li>

<li>M. Belhaj, P. Protopapas, W. Pan. "Deep variational transfer: Transfer learning through semi-supervised deep generative models." arXiv preprint arXiv:1812.03123 (2018).</li>

<li>J.R. Maat, N. Gianniotis, P. Protopapas. "Efficient optimization of echo state networks for time series datasets." 2018 International Joint Conference on Neural Networks (IJCNN), 1-7 (2018).</li>

<li>N. Hoernle, K. Gal, B. Grosz, P. Protopapas, A. Rubin. "Modeling the Effects of Students' Interactions with Immersive Simulations Using Markov Switching Systems." International Educational Data Mining Society (2018).</li>

<li>J.R. Martínez-Galarza, P. Protopapas, H.A. Smith, E.F. Morales. "Unraveling the Spectral Energy Distributions of Clustered YSOs." The Astrophysical Journal 864(1), 71 (2018).</li>

<li>R.C. Davis, G. Cabrera-Vives, F. Förster, P.A. Estévez, P. Huijse, P. Protopapas, I. Reyes, J. Martínez, C. Donoso. "Deep Learning for Image Sequence Classification of Astronomical Events." arXiv preprint arXiv:1807.03869 (2018).</li>

<li>Y.F. Jiang, P.J. Green, J.E. Greene, E. Morganson, Y. Shen, A. Pancoast, C.L. MacLeod, S.F. Anderson, W.N. Brandt, C.J. Grier, H.W. Rix. "Detection of time lags between quasar continuum emission bands based on Pan-STARRS light curves." The Astrophysical Journal 836(2), 186 (2017).</li>

<li>P. Benavente, P. Protopapas, K. Pichara. "Automatic survey-invariant classification of variable stars." The Astrophysical Journal 845(2), 147 (2017).</li>

<li>Yago Bea, Raúl Jiménez, David Mateos, Shuheng Liu, Pavlos Protopapas, Pedro Tarancón-Álvarez, Pablo Tejerina-Pérez. "Gravitational Duals from Equations of State." arXiv preprint arXiv:2403.14763 (2024).</li>

<li>John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin. "IoT Malware Data Augmentation using a Generative Adversarial Network." HICSS 2024: 7572-7581.</li>

<li>John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin. "Behavioral Malware Detection using a Language Model Classifier Trained on sys2vec Embeddings." HICSS 2024: 7582-7591.</li>

<li>Marios Mattheakis, Hayden Joy, Pavlos Protopapas. "A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function." CoRR abs/2101.06100 (2021) (Note: This appears to be a journal publication in 2023 of a 2021 preprint).</li>

<li>R Pellegrin, B Bullwinkel, M Mattheakis, P Protopapas. "Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows" (2023)</li>

<li>O Graf, P Flores, P Protopapas, K Pichara. "Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks" (2023)</li>

<li>Blake Bullwinkel, Dylan Randle, Pavlos Protopapas, David Sondak. "Deqgan: Learning the loss function for pinns with generative adversarial networks" (2023)</li>

<li>S Liu, X Huang, P Protopapas. "Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems" (2023)</li>

<li>Hayden Joy, Marios Mattheakis, Pavlos Protopapas. "RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization" (2023)</li>

<li>F Förster, G Cabrera-Vives, E Castillo-Navarrete, PA Estévez, ... P Protopapas, et al. "The automatic learning for the rapid classification of events (ALeRCE) alert broker" (2021)</li>

<li>M Mattheakis, D Sondak, AS Dogra, P Protopapas. "Hamiltonian neural networks for solving equations of motion" (2022)</li>

<li>Pellegrin, R., Bullwinkel, B., Mattheakis, M., Protopapas, P., "Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows" (2023)</li>

<li>Graf, O., Flores, P., Protopapas, P., Pichara, K., "Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks" (2023)</li>

<li>Bullwinkel, B., Randle, D., Protopapas, P., Sondak, D., "Deqgan: Learning the loss function for pinns with generative adversarial networks" (2023)</li>

<li>Liu, S., Huang, X., Protopapas, P., "Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems" (2023)</li>

<li>Joy, H., Mattheakis, M., Protopapas, P., "RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization" (2023)</li>

<li>Förster, F., Cabrera-Vives, G., Castillo-Navarrete, E., Estévez, P.A., ... Protopapas, P., et al., "The automatic learning for the rapid classification of events (ALeRCE) alert broker" (2021)</li>

<li>Mattheakis, M., Sondak, D., Dogra, A.S., Protopapas, P., "Hamiltonian neural networks for solving equations of motion" (2022)</li>
<li>
Ferreira, T. A. E., Mattheakis, M., and Protopapas, P., <em>A New Artificial
Neuron Proposal with Trainable Simultaneous Local and Global Activation Function</em>, 2021, <i>arXiv:2101.06100</i> [<a href="Pub/Tiago2021.pdf">pdf</a>]
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