CODEBench: A Neural Architecture and Hardware Accelerator Co-Design Framework

7 December 2022

Papers citing "CODEBench: A Neural Architecture and Hardware Accelerator Co-Design Framework"

5 / 5 papers shown

Title
EdgeTran: Co-designing Transformers for Efficient Inference on Mobile Edge Platforms Shikhar Tuli N. Jha 19 3 0 24 Mar 2023
Efficient Multi-objective Neural Architecture Search via Lamarckian Evolution T. Elsken J. H. Metzen Frank Hutter 117 498 0 24 Apr 2018
Xception: Deep Learning with Depthwise Separable Convolutions François Chollet MDE BDL PINN 198 14,190 0 07 Oct 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu L. V. D. van der Maaten Kilian Q. Weinberger PINN 3DV 244 35,884 0 25 Aug 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015