Partha Maji - RankMe

16 papers A 1Journal 9Unranked 5

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Enabling ImageNet-Scale Deep Learning on MCUs for Accurate and Efficient Inference. IEEE Internet Things J. Sulaiman Sadiq, Jonathon S. Hare, Simon Craske, Partha Maji, Geoff V. Merrett
2022	—	`conf`	TinyOps: ImageNet Scale Deep Learning on Microcontrollers. CVPR Workshops Sulaiman Sadiq, Jonathon S. Hare, Partha Maji, Simon Craske, Geoff V. Merrett
2021	J	`jnl`	An Underexplored Dilemma between Confidence and Calibration in Quantized Neural Networks. CoRR Guoxuan Xia, Sangwon Ha, Tiago Azevedo, Partha Maji
2021	J	`jnl`	On Efficient Uncertainty Estimation for Resource-Constrained Mobile Applications. CoRR Johanna Rock, Tiago Azevedo, René de Jong, Daniel Ruiz-Muñoz, Partha Maji
2021	J	`jnl`	On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks. CoRR Martin Ferianc, Partha Maji, Matthew Mattina, Miguel Rodrigues
2021	A	`conf`	On the effects of quantisation on model uncertainty in Bayesian neural networks. UAI Martin Ferianc, Partha Maji, Matthew Mattina, Miguel Rodrigues
2021	J	`jnl`	Stochastic-Shield: A Probabilistic Approach Towards Training-Free Adversarial Defense in Quantized CNNs. CoRR Lorena Qendro, Sangwon Ha, René de Jong, Partha Maji
2021	—	`conf`	Towards Efficient Point Cloud Graph Neural Networks Through Architectural Simplification. ICCVW Shyam A. Tailor, René de Jong, Tiago Azevedo, Matthew Mattina, Partha Maji
2021	J	`jnl`	Towards Efficient Point Cloud Graph Neural Networks Through Architectural Simplification. CoRR Shyam A. Tailor, René de Jong, Tiago Azevedo, Matthew Mattina, Partha Maji
2020	—	`—`	Model-architecture co-design of deep neural networks for embedded systems. Partha Maji
2020	J	`jnl`	Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset Shifts. CoRR Tiago Azevedo, René de Jong, Partha Maji
2019	—	`conf`	Efficient Winograd or Cook-Toom Convolution Kernel Implementation on Widely Used Mobile CPUs. EMC2@HPCA/CVPR/ISCA Partha Maji, Andrew Mundy, Ganesh Dasika, Jesse G. Beu, Matthew Mattina, Robert Mullins
2019	J	`jnl`	Efficient Winograd or Cook-Toom Convolution Kernel Implementation on Widely Used Mobile CPUs. CoRR Partha Maji, Andrew Mundy, Ganesh Dasika, Jesse G. Beu, Matthew Mattina, Robert Mullins
2018	J	`jnl`	On the Reduction of Computational Complexity of Deep Convolutional Neural Networks. Entropy Partha Maji, Robert Mullins
2017	—	`conf`	1D-FALCON: Accelerating Deep Convolutional Neural Network Inference by Co-optimization of Models and Underlying Arithmetic Implementation. ICANN (2) Partha Maji, Robert Mullins
2017	—	`conf`	ADaPT: optimizing CNN inference on IoT and mobile devices using approximately separable 1-D kernels. IML Partha Maji, Daniel Bates, Alexandra W. Chadwick, Robert Mullins