Rlalign: a reinforcement learning approach for multiple sequence alignment RK Ramakrishnan, J Singh, M Blanchette 2018 IEEE 18th International Conference on Bioinformatics and Bioengineering …, 2018 | 22 | 2018 |
Differentiable mask for pruning convolutional and recurrent networks RK Ramakrishnan, E Sari, VP Nia 2020 17th Conference on Computer and Robot Vision (CRV), 222-229, 2020 | 16 | 2020 |
An empirical study of low precision quantization for tinyml S Zhuo, H Chen, RK Ramakrishnan, T Chen, C Feng, Y Lin, P Zhang, ... arXiv preprint arXiv:2203.05492, 2022 | 10 | 2022 |
Deep demosaicing for edge implementation R Ramakrishnan, S Jui, V Partovi Nia Image Analysis and Recognition: 16th International Conference, ICIAR 2019 …, 2019 | 4 | 2019 |
Neural network pruning VP NIA, RK Ramakrishnan, EH Sari US Patent App. 17/012,818, 2021 | 1 | 2021 |
Tensor train decompositions on recurrent networks A Murua, R Ramakrishnan, X Li, RH Yang, VP Nia arXiv preprint arXiv:2006.05442, 2020 | 1 | 2020 |
Differentiable Mask Pruning for Neural Networks. RK Ramakrishnan, E Sari, VP Nia CoRR, 2019 | 1 | 2019 |
Exploring Reinforcement Learning Techniques in Multiple Sequence Alignment RK Ramakrishnan McGill University (Canada), 2018 | 1 | 2018 |
[Regular Paper] Detection of Errors in Multi-genome Alignments Using Machine Learning Approaches J Singh, RK Ramakrishnan, M Blanchette 2018 IEEE 18th International Conference on Bioinformatics and Bioengineering …, 2018 | | 2018 |
Deep Demosaicing RK Ramakrishnan, S Jui, VP Nia | | |