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PredictiveNet: An energy-efficient convolutional neural network via zero prediction.

, , , and . ISCAS, page 1-4. IEEE, (2017)

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Analytical Guarantees on Numerical Precision of Deep Neural Networks., , and . ICML, volume 70 of Proceedings of Machine Learning Research, page 3007-3016. PMLR, (2017)Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training., , , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 19123-19138. PMLR, (2022)Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks., , , , , , and . ICLR (Poster), OpenReview.net, (2019)True Gradient-Based Training of Deep Binary Activated Neural Networks Via Continuous Binarization., , , , and . ICASSP, page 2346-2350. IEEE, (2018)VaPr: Variable-Precision Tensors to Accelerate Robot Motion Planning., , , , , , , and . IROS, page 6304-6309. (2023)Optimizing Selective Protection for CNN Resilience., , , , , , , , , and . ISSRE, page 127-138. IEEE, (2021)KeyRAM: A 0.34 uJ/decision 18 k decisions/s Recurrent Attention In-memory Processor for Keyword Spotting., , , and . CICC, page 1-4. IEEE, (2020)Fundamental Limits on the Precision of In-memory Architectures., , , and . ICCAD, page 128:1-128:9. IEEE, (2020)Fundamental Limits on Energy-Delay-Accuracy of In-memory Architectures in Inference Applications., , , and . CoRR, (2020)HarDNN: Feature Map Vulnerability Evaluation in CNNs., , , , , , , , , and . CoRR, (2020)