Publications

Syrine Belakaria, Aryan Deshwal, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa (2020). Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization.. AAAI.

Nitthilan Kanappan Jayakodi, Janardhan Rao Doppa, Partha Pratim Pande (2020). PETNet: Polycount and Energy Trade-off Deep Networks for Producing 3D Objects from Images. 2020 57th ACM/IEEE Design Automation Conference (DAC).

Biresh Kumar Joardar, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa, Hai Li, Partha Pratim Pande, Krishnendu Chakrabarty (2020). GRAMARCH: A GPU-ReRAM based Heterogeneous Architecture for Neural Image Segmentation. 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE).

Nitthilan Kanappan Jayakodi, Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa (2020). Design and Optimization of Energy-Accuracy Tradeoff Networks for Mobile Platforms via Pretrained Deep Models. ACM Transactions on Embedded Computing Systems (TECS).

Nitthilan Kannappan Jayakodi, Anwesha Chatterjee, Wonje Choi, Janardhan Rao Doppa, Partha Pratim Pande (2019). Trading-off Accuracy and Energy of Deep Inference on Embedded Systems: A Co-Design Approach. arXiv.

Aryan Deshwal, Nitthilan Kanappan Jayakodi, Biresh Kumar Joardar, Janardhan Rao Doppa, Partha Pratim Pande (2019). MOOS: A multi-objective design space exploration and optimization framework for NoC enabled manycore systems. ACM Transactions on Embedded Computing Systems (TECS).

Shubhomoy Das, Md Rakibul Islam, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa (2019). Active Anomaly Detection via Ensembles: Insights, Algorithms, and Interpretability. arXiv preprint arXiv:1901.08930.

Nitthilan Kannappan Jayakodi, Anwesha Chatterjee, Wonje Choi, Janardhan Rao Doppa, Partha Pratim Pande (2018). Trading-off accuracy and energy of deep inference on embedded systems: A co-design approach. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

Shubhomoy Das, Md Rakibul Islam, Nitthilan Kannappan Jayakodi, Janardhan Rao Doppa (2018). Active anomaly detection via ensembles. arXiv preprint arXiv:1809.06477.