| Harnessing the power of CNNs for unevenly-sampled light-curves using Markov Transition Field M Bugueno, G Molina, F Mena, P Olivares, M Araya Astronomy and Computing 35, 100461, 2021 | 18 | 2021 |
| A binary variational autoencoder for hashing F Mena, R Nanculef Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2019 | 11 | 2019 |
| Refining exoplanet detection using supervised learning and feature engineering M Bugueno, F Mena, M Araya 2018 XLIV Latin American Computer Conference (CLEI), 278-287, 2018 | 11 | 2018 |
| Common practices and taxonomy in deep multi-view fusion for remote sensing applications F Mena, D Arenas, M Nuske, A Dengel IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024 | 5 | 2024 |
| Self-supervised bernoulli autoencoders for semi-supervised hashing R Ñanculef, F Mena, A Macaluso, S Lodi, C Sartori Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2021 | 4 | 2021 |
| Predicting Crop Yield with Machine Learning: An Extensive Analysis of Input Modalities and Models on a Field and Sub-Field Level D Pathak, M Miranda, F Mena, C Sanchez, P Helber, B Bischke, ... IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium …, 2023 | 3 | 2023 |
| A Comparative Assessment of Multi-view fusion learning for Crop Classification F Mena, D Arenas, M Nuske, A Dengel IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium …, 2023 | 3 | 2023 |
| On the Quality of Deep Representations for Kepler Light Curves Using Variational Auto-Encoders F Mena, P Olivares, M Bugueño, G Molina, M Araya Signals 2 (4), 706-728, 2021 | 2 | 2021 |
| Adaptive Fusion of Multi-view Remote Sensing data for Optimal Sub-field Crop Yield Prediction F Mena, D Pathak, H Najjar, C Sanchez, P Helber, B Bischke, P Habelitz, ... arXiv preprint arXiv:2401.11844, 2024 | 1 | 2024 |
| Interpretable and effective hashing via Bernoulli variational auto-encoders F Mena, R Ñanculef, C Valle Intelligent Data Analysis 24 (S1), 141-166, 2020 | 1 | 2020 |
| Revisiting Machine Learning from Crowds a Mixture Model for Grouping Annotations F Mena, R Ñanculef Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2019 | 1 | 2019 |
| In the Search for Optimal Multi-view Learning Models for Crop Classification with Global Remote Sensing Data F Mena, D Arenas, A Dengel arXiv preprint arXiv:2403.16582, 2024 | | 2024 |
| Impact Assessment of Missing Data in Model Predictions for Earth Observation Applications F Mena, D Arenas, M Charfuelan, M Nuske, A Dengel arXiv preprint arXiv:2403.14297, 2024 | | 2024 |
| Can we Interpret Machine Learning? An Analysis of Exoplanet Detection Problem G Molina, F Mena, M Bugueño, M Solar Astronomical Data Analysis Software and Systems XXIX 527, 183, 2020 | | 2020 |
| Collective annotation patterns in learning from crowds F Mena, R Ñanculef, C Valle Intelligent Data Analysis 24 (S1), 63-86, 2020 | | 2020 |
| Classical Machine Learning Techniques in the Search of Extrasolar Planets FA Mena, MC Bugueño, M Araya CLEI electronic journal 22 (3), 3: 1-3: 18, 2019 | | 2019 |
| Evaluating Bregman Divergences for Probability Learning from Crowd FA Mena, R Nanculef arXiv preprint arXiv:1901.10653, 2019 | | 2019 |
Margarita Constanza Bugueño PérezHasso-Plattner Institute (HPI), University of PotsdamAdresse e-mail validée de sansano.usm.cl
