| High-performance video content recognition with long-term recurrent convolutional network for FPGA X Zhang, X Liu, A Ramachandran, C Zhuge, S Tang, P Ouyang, Z Cheng, ... 2017 27th International Conference on Field Programmable Logic and …, 2017 | 103 | 2017 |
| Machine learning on FPGAs to face the IoT revolution X Zhang, A Ramachandran, C Zhuge, D He, W Zuo, Z Cheng, K Rupnow, ... 2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 894-901, 2017 | 84 | 2017 |
| Hardware acceleration of the pair-HMM algorithm for DNA variant calling S Huang, GJ Manikandan, A Ramachandran, K Rupnow, WW Hwu, ... Proceedings of the 2017 ACM/SIGDA International Symposium on Field …, 2017 | 73 | 2017 |
| BLESS 2: accurate, memory-efficient and fast error correction method Y Heo, A Ramachandran, WM Hwu, J Ma, D Chen Bioinformatics 32 (15), 2369-2371, 2016 | 37 | 2016 |
| Xtream-fit: an energy-delay efficient data memory subsystem for embedded media processing A Ramachandran, MF Jacome Proceedings of the 40th annual Design Automation Conference, 137-142, 2003 | 26 | 2003 |
| FPGA accelerated DNA error correction A Ramachandran, Y Heo, W Hwu, J Ma, D Chen 2015 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2015 | 22 | 2015 |
| HELLO: improved neural network architectures and methodologies for small variant calling A Ramachandran, SS Lumetta, EW Klee, D Chen BMC bioinformatics 22, 1-31, 2021 | 13 | 2021 |
| GPU acceleration of advanced k-mer counting for computational genomics H Li, A Ramachandran, D Chen 2018 IEEE 29th International Conference on Application-specific Systems …, 2018 | 9 | 2018 |
| Energy-delay efficient data memory subsystems: suitable for embedded media" processing" A Ramachandran, MF Jacome IEEE Signal Processing Magazine 22 (3), 23-37, 2005 | 9 | 2005 |
| Deep learning for better variant calling for cancer diagnosis and treatment A Ramachandran, H Li, E Klee, SS Lumetta, D Chen 2018 23rd Asia and South Pacific Design Automation Conference (ASP-DAC), 16-21, 2018 | 5 | 2018 |
| Comprehensive evaluation of error-correction methodologies for genome sequencing data Y Heo, G Manikandan, A Ramachandran, D Chen Exon Publications, 89-108, 2021 | 4 | 2021 |
| HELLO: A hybrid variant calling approach A Ramachandran, SS Lumetta, E Klee, D Chen bioRxiv, 2020.03. 23.004473, 2020 | 3 | 2020 |
| Power aware embedded computing MF Jacome, A Ramachandran Embedded Systems Handbook: Embedded Systems Design and Verification, 2018 | 3 | 2018 |
| Learning to Retrieve Engaging Follow-Up Queries C Richardson, S Kar, A Kumar, A Ramachandran, OZ Khan, Z Raeesy, ... arXiv, 2023 | 2 | 2023 |
| Comprehensive assessment of error correction methods for high-throughput sequencing data Y Heo, G Manikandan, A Ramachandran, D Chen arXiv preprint arXiv:2007.05121, 2020 | 2 | 2020 |
| A recurrent Markov state-space generative model for sequences A Ramachandran, S Lumetta, E Klee, D Chen The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 2 | 2019 |
| PandoGen: Generating complete instances of future SARS-CoV-2 sequences using Deep Learning A Ramachandran, SS Lumetta, D Chen PLoS computational biology 20 (1), e1011790, 2024 | 1 | 2024 |
| Energy-aware embedded media processing [electronic resource]: customizable memory subsystems and energy management policies A Ramachandran, MF Jacome The University of Texas at Austin, 2006 | | 2006 |
| Energy-aware embedded media processing: customizable memory subsystems and energy management policies A Ramachandran The University of Texas at Austin, 2004 | | 2004 |
