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When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA.

, , , , , , and . DAC, page 1-6. IEEE, (2023)

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Recurrent Neural Networks With Column-Wise Matrix-Vector Multiplication on FPGAs., , , , , , , , , and . IEEE Trans. Very Large Scale Integr. Syst., 30 (2): 227-237 (2022)FPGA-Based Acceleration for Bayesian Convolutional Neural Networks., , , , , , and . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 41 (12): 5343-5356 (2022)In-circuit tuning of deep learning designs., , , , , and . J. Syst. Archit., (2021)Customizable FPGA-based Accelerator for Binarized Graph Neural Networks., , , and . ISCAS, page 1968-1972. IEEE, (2022)F-E3D: FPGA-based Acceleration of an Efficient 3D Convolutional Neural Network for Human Action Recognition., , , , , , , and . ASAP, page 1-8. IEEE, (2019)Applications and Techniques for Fast Machine Learning in Science., , , , , , , , , and 77 other author(s). CoRR, (2021)Memory-Efficient Architecture for Accelerating Generative Networks on FPGA., , , , , , , and . FPT, page 30-37. IEEE, (2018)An Overlay for Rapid FPGA Debug of Machine Learning Applications., , , , , and . FPT, page 135-143. IEEE, (2019)An efficient convolutional neural network for small traffic sign detection., , , , and . J. Syst. Archit., (2019)Optimizing Reconfigurable Recurrent Neural Networks., , , , , , , and . FCCM, page 10-18. IEEE, (2020)