| Adversary Resistant Deep Neural Networks with an Application to Malware Detection Q Wang, W Guo, K Zhang, AG Ororbia, X Xing, X Liu, CL Giles Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 230 | 2017 |
| A Neural Temporal Model for Human Motion Prediction A Gopalakrishnan, A Mali, D Kifer, L Giles, AG Ororbia Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 198 | 2019 |
| CiteSeerX: AI in a Digital Library Search Engine. J Wu, K Williams, HH Chen, M Khabsa, C Caragea, AG Ororbia, D Jordan, ... AAAI, 2930-2937, 2014 | 162 | 2014 |
| CiteSeerX: AI in a digital library search engine J Wu, K William, HH Chen, M Khabsa, C Caragea, S Tuarob, AG Ororbia, ... AI Magazine 36 (3), 35-49, 2015 | 157 | 2015 |
| Using Prerequisites to Extract Concept Maps fromTextbooks S Wang, AG Ororbia, Z Wu, K Williams, C Liang, B Pursel, CL Giles Proceedings of the 25th ACM International on Conference on Information and …, 2016 | 124 | 2016 |
| Biologically Motivated Algorithms for Propagating Local Target Representations AG Ororbia, A Mali Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4651-4658, 2018 | 98 | 2018 |
| Multi-scale FCN with Cascaded Instance Aware Segmentation for Arbitrary Oriented Word Spotting in the Wild. D He, X Yang, C Liang, Z Zhou, AG Ororbia, D Kifer, CL Giles CVPR, 474-483, 2017 | 95 | 2017 |
| Learning a Hierarchical Latent-Variable Model of 3D Shapes S Liu, L Giles, AG Ororbia 2018 International Conference on 3D Vision (3DV), 542-551, 2018 | 90 | 2018 |
| Continual learning of recurrent neural networks by locally aligning distributed representations A Ororbia, A Mali, CL Giles, D Kifer IEEE Transactions on Neural Networks and Learning Systems, 2020 | 84* | 2020 |
| An Empirical Evaluation of Rule Extraction from Recurrent Neural Networks Q Wang, K Zhang, AG Ororbia, X Xing, X Liu, CL Giles Neural computation 30 (9), 2568-2591, 2018 | 83* | 2018 |
| Learning simpler language models with the differential state framework AG Ororbia, T Mikolov, D Reitter Neural Computation, 1-26, 2017 | 80 | 2017 |
| The neural coding framework for learning generative models A Ororbia, D Kifer Nature Communications 13 (1), 1-14, 2022 | 79 | 2022 |
| Towards building a scholarly big data platform: Challenges, lessons and opportunities Z Wu, J Wu, M Khabsa, K Williams, HH Chen, W Huang, S Tuarob, ... Digital Libraries (JCDL), 2014 IEEE/ACM Joint Conference on, 117-126, 2014 | 72 | 2014 |
| Smart library: identifying books on library shelves using supervised deep learning for scene text reading X Yang, D He, W Huang, AG Ororbia, Z Zhou, D Kifer, CL Giles Proceedings of the 17th ACM/IEEE Joint Conference on Digital Libraries, 245-248, 2017 | 65* | 2017 |
| Investigating Recurrent Neural Network Memory Structures using Neuro-evolution AG Ororbia, AER ElSaid, T Desell Proceedings of the Genetic and Evolutionary Computation Conference, 446-455, 2019 | 64 | 2019 |
| Fbert: A neural transformer for identifying offensive content D Sarkar, M Zampieri, T Ranasinghe, A Ororbia Findings of the Association for Computational Linguistics: EMNLP 2021, 2021 | 60 | 2021 |
| Learning Adversary-Resistant Deep Neural Networks Q Wang, W Guo, K Zhang, AG Ororbia, X Xing, CL Giles, X Liu https://arxiv.org/abs/1612.01401, 2016 | 60 | 2016 |
| Unifying Adversarial Training Algorithms with Data Gradient Regularization AG Ororbia, D Kifer, CL Giles Neural computation 29 (4), 867-887, 2017 | 57* | 2017 |
| Piecewise Latent Variables for Neural Variational Text Processing IV Serban, AG Ororbia, J Pineau, A Courville Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017 | 56* | 2017 |
| The Predictive Forward-Forward Algorithm AG Ororbia, A Mali https://arxiv.org/abs/2301.01452, 2023 | 40 | 2023 |
C Lee GilesPennsylvania State UniversityZweryfikowany adres z psu.edu