| Modeling tabular data using conditional gan L Xu, M Skoularidou, A Cuesta-Infante, K Veeramachaneni Advances in neural information processing systems 32, 2019 | 1726 | 2019 |
| Tadgan: Time series anomaly detection using generative adversarial networks A Geiger, D Liu, S Alnegheimish, A Cuesta-Infante, K Veeramachaneni 2020 ieee international conference on big data (big data), 33-43, 2020 | 392 | 2020 |
| Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications JM Górriz, J Ramírez, A Ortíz, FJ Martinez-Murcia, F Segovia, J Suckling, ... Neurocomputing 410, 237-270, 2020 | 308 | 2020 |
| SteganoGAN: High capacity image steganography with GANs KA Zhang, A Cuesta-Infante, L Xu, K Veeramachaneni arXiv preprint arXiv:1901.03892, 2019 | 298 | 2019 |
| ATM: A distributed, collaborative, scalable system for automated machine learning T Swearingen, W Drevo, B Cyphers, A Cuesta-Infante, A Ross, ... 2017 IEEE international conference on big data (big data), 151-162, 2017 | 154 | 2017 |
| Robust invisible video watermarking with attention KA Zhang, L Xu, A Cuesta-Infante, K Veeramachaneni arXiv preprint arXiv:1909.01285, 2019 | 111 | 2019 |
| glUCModel: A monitoring and modeling system for chronic diseases applied to diabetes JI Hidalgo, E Maqueda, JL Risco-Martín, A Cuesta-Infante, JM Colmenar, ... Journal of biomedical informatics 48, 183-192, 2014 | 79 | 2014 |
| Mobile robot path planning using a QAPF learning algorithm for known and unknown environments U Orozco-Rosas, K Picos, JJ Pantrigo, AS Montemayor, A Cuesta-Infante IEEE Access 10, 84648-84663, 2022 | 71 | 2022 |
| Learning vine copula models for synthetic data generation Y Sun, A Cuesta-Infante, K Veeramachaneni Proceedings of the aaai conference on artificial intelligence 33 (01), 5049-5057, 2019 | 67 | 2019 |
| Modeling glycemia in humans by means of grammatical evolution JI Hidalgo, JM Colmenar, JL Risco-Martin, A Cuesta-Infante, E Maqueda, ... Applied Soft Computing 20, 40-53, 2014 | 48 | 2014 |
| Modeling tabular data using conditional gan. arXiv 2019 L Xu, M Skoularidou, A Cuesta-Infante, K Veeramachaneni arXiv preprint arXiv:1907.00503 1, 2019 | 47 | 2019 |
| Learning representations for log data in cybersecurity I Arnaldo, A Cuesta-Infante, A Arun, M Lam, C Bassias, ... Cyber Security Cryptography and Machine Learning: First International …, 2017 | 33 | 2017 |
| Bayesian capsule networks for 3D human pose estimation from single 2D images I Ramirez, A Cuesta-Infante, E Schiavi, JJ Pantrigo Neurocomputing 379, 64-73, 2020 | 30 | 2020 |
| Bivariate empirical and n-variate archimedean copulas in estimation of distribution algorithms A Cuesta-Infante, R Santana, JI Hidalgo, C Bielza, P Larrañaga IEEE Congress on Evolutionary Computation, 1-8, 2010 | 27 | 2010 |
| Convolutional neural networks for computer vision-based detection and recognition of dumpsters I Ramirez, A Cuesta-Infante, JJ Pantrigo, AS Montemayor, JL Moreno, ... Neural Computing and Applications 32 (17), 13203-13211, 2020 | 23 | 2020 |
| Modeling tabular data using conditional GAN. 2019 L Xu, M Skoularidou, A Cuesta-Infante, K Veeramachaneni arXiv preprint arXiv:1907.00503, 1907 | 21 | 1907 |
| Lightweight tracking-by-detection system for multiple pedestrian targets B Lacabex, A Cuesta-Infante, AS Montemayor, JJ Pantrigo Integrated computer-aided engineering 23 (3), 299-311, 2016 | 17 | 2016 |
| Sample, estimate, tune: Scaling bayesian auto-tuning of data science pipelines A Anderson, S Dubois, A Cuesta-Infante, K Veeramachaneni 2017 IEEE International Conference on Data Science and Advanced Analytics …, 2017 | 15 | 2017 |
| Steganogan: Pushing the limits of image steganography KA Zhang, A Cuesta-Infante, K Veeramachaneni arXiv preprint arXiv:1901.03892 2, 2019 | 13 | 2019 |
| Fast incremental learning by transfer learning and hierarchical sequencing L Llopis-Ibor, C Beltran-Royo, A Cuesta-Infante, JJ Pantrigo Expert Systems with Applications 212, 118580, 2023 | 12 | 2023 |
Kalyan VeeramachaneniPrincipal Research Scientist, Massachusetts Institute of TechnologyE-mail megerősítve itt: csail.mit.edu