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ODE-Inspired Network Design for Single Image Super-Resolution.

, , , , , and . CVPR, page 1732-1741. Computer Vision Foundation / IEEE, (2019)

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A System-Level Solution for Low-Power Object Detection., , , , , , , , , and 1 other author(s). ICCV Workshops, page 2461-2468. IEEE, (2019)A2Q: Aggregation-Aware Quantization for Graph Neural Networks., , , , , , , and . CoRR, (2023)GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks., , , and . NeurIPS, (2022)MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization., , , , , , , and . CoRR, (2023)ODE-Inspired Network Design for Single Image Super-Resolution., , , , , and . CVPR, page 1732-1741. Computer Vision Foundation / IEEE, (2019)MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization., , , , , , , and . HPCA, page 124-138. IEEE, (2024)Ladder Pyramid Networks For Single Image Super-Resolution., , , and . ICIP, page 578-582. IEEE, (2020)ProxyBNN: Learning Binarized Neural Networks via Proxy Matrices., , , , , , , and . ECCV (3), volume 12348 of Lecture Notes in Computer Science, page 223-241. Springer, (2020)$A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks., , , , , , , and . ICLR, OpenReview.net, (2023)