| A ReLU dense layer to improve the performance of neural networks AM Javid, S Das, M Skoglund, S Chatterjee ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 49 | 2021 |
| Progressive learning for systematic design of large neural networks S Chatterjee, AM Javid, M Sadeghi, PP Mitra, M Skoglund arXiv preprint arXiv:1710.08177, 2017 | 33 | 2017 |
| Predictive analysis of COVID-19 time-series data from Johns Hopkins University AM Javid, X Liang, A Venkitaraman, S Chatterjee arXiv preprint arXiv:2005.05060, 2020 | 15 | 2020 |
| Asynchrounous decentralized learning of a neural network X Liang, AM Javid, M Skoglund, S Chatterjee ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 14 | 2020 |
| Distributed large neural network with centralized equivalence X Liang, AM Javid, M Skoglund, S Chatterjee 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 14 | 2018 |
| SSFN--Self Size-estimating Feed-forward Network with Low Complexity, Limited Need for Human Intervention, and Consistent Behaviour across Trials S Chatterjee, AM Javid, M Sadeghi, S Kikuta, D Liu, PP Mitra, M Skoglund arXiv preprint arXiv:1905.07111, 2019 | 11 | 2019 |
| Decentralized learning of randomization-based neural networks with centralized equivalence X Liang, AM Javid, M Skoglund, S Chatterjee Applied Soft Computing 115, 108030, 2022 | 8 | 2022 |
| SSFN: Self size-estimating feed-forward network and low complexity design S Chatterjee, AM Javid, SKM Sadeghi, PP Mitra, M Skoglund arXiv preprint arXiv:1905.07111, 2019 | 8 | 2019 |
| A low complexity decentralized neural net with centralized equivalence using layer-wise learning X Liang, AM Javid, M Skoglund, S Chatterjee 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 6 | 2020 |
| Determination of the design parameters for making urban wastewater plants in cold regions of Iran SR Jazayeri, M Sadeghi, AH EHSANI, A Javid Journal of Shahrekord University of Medical Sciences 11 (4), 92-100, 2010 | 6 | 2010 |
| Mutual information preserving analysis of a single layer feedforward network AM Javid, S Chatterjee, M Skoglund 2018 15th International Symposium on Wireless Communication Systems (ISWCS), 1-5, 2018 | 5 | 2018 |
| Neural greedy pursuit for feature selection S Das, AM Javid, PB Gohain, YC Eldar, S Chatterjee 2022 International Joint Conference on Neural Networks (IJCNN), 1-7, 2022 | 3 | 2022 |
| Use of deterministic transforms to design weight matrices of a neural network PG Jurado, X Liang, AM Javid, S Chatterjee 2021 29th European Signal Processing Conference (EUSIPCO), 1366-1370, 2021 | 3 | 2021 |
| High-dimensional neural feature using rectified linear unit and random matrix instance AM Javid, A Venkitaraman, M Skoglund, S Chatterjee ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 3 | 2020 |
| Learning without Forgetting for Decentralized Neural Nets with Low Communication Overhead X Liang, AM Javid, M Skoglund, S Chatterjee 2020 28th European Signal Processing Conference (EUSIPCO), 2185-2189, 2021 | 2 | 2021 |
| Neural network architecture design: towards low-complexity and scalable solutions A M Javid KTH Royal Institute of Technology, 2021 | 2 | 2021 |
| High-dimensional neural feature design for layer-wise reduction of training cost AM Javid, A Venkitaraman, M Skoglund, S Chatterjee arXiv preprint arXiv:2003.13058, 2020 | 2 | 2020 |
| R3Net: random weights, rectifier linear units and robustness for artificial neural network A Venkitaraman, AM Javid, S Chatterjee arXiv preprint arXiv:1803.04186, 2018 | 2 | 2018 |
| Analysis of network coding in a slotted ALOHA-based two-way relay network AM Javid, M Setayesh, F Farhadi, F Ashtiani arXiv preprint arXiv:1602.02041, 2016 | 2 | 2016 |
| Adaptive Learning without Forgetting via Low-Complexity Convex Networks AM Javid, X Liang, M Skoglund, S Chatterjee 2020 28th European Signal Processing Conference (EUSIPCO), 1623-1627, 2021 | 1 | 2021 |
Saikat ChatterjeeKTH - Royal Institute of TechnologyVerified email at kth.se
