DeepGO: Predicting protein functions from sequence and interactions using a deep ontology-aware classifier M Kulmanov, MA Khan, R Hoehndorf Bioinformatics, btx624, 2017 | 138 | 2017 |
Neuro-symbolic representation learning on biological knowledge graphs M Alshahrani, MA Khan, O Maddouri, AR Kinjo, N Queralt-Rosinach, ... Bioinformatics 33 (17), 2723-2730, 2017 | 76 | 2017 |
Robust energy-based least squares twin support vector machines M Tanveer, MA Khan, SS Ho Applied Intelligence 45 (1), 174-186, 2016 | 51 | 2016 |
Learning based primary user activity prediction in cognitive radio networks for efficient dynamic spectrum access A Agarwal, S Dubey, MA Khan, R Gangopadhyay, S Debnath 2016 International Conference on Signal Processing and Communications (SPCOM …, 2016 | 38 | 2016 |
Incorporating Literals into Knowledge Graph Embeddings A Kristiadi*, MA Khan*, D Lukovnikov, J Lehmann, A Fischer International Semantic Web Conference. Springer, 2019 | 27 | 2019 |
Utilizing Temporal Information in Deep Convolutional Network for Efficient Soccer Ball Detection and Tracking A Kukleva*, MA Khan*, H Farazi, S Behnke 23rd RoboCup International Symposium, 2019 | 5 | 2019 |
Unsupervised Cross-Domain Speech-to-Speech Conversion with Time-Frequency Consistency MA Khan, F Cardinaux, S Uhlich, M Ferras, A Fischer arXiv preprint arXiv:2005.07810, 2020 | | 2020 |
Predicting protein functions from sequence and interactions using a neuro-symbolic deep learning model M Kulmanov, MA Khan, R Hoehndorf F1000Research 6, 2017 | | 2017 |