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NEBULA: A Neuromorphic Spin-Based Ultra-Low Power Architecture for SNNs and ANNs., , , , , , , , and . ISCA, page 363-376. IEEE, (2020)An ASIP for image enhancement applications in spatial domain using LISA., , , and . ReTIS, page 175-179. IEEE, (2011)Exploiting Activation based Gradient Output Sparsity to Accelerate Backpropagation in CNNs., , , , , , , and . CoRR, (2021)Structured in Space, Randomized in Time: Leveraging Dropout in RNNs for Efficient Training., , , , , and . NeurIPS, page 24545-24555. (2021)A Learning-Guided Hierarchical Approach for Biomedical Image Segmentation., , , , , , and . SoCC, page 227-232. IEEE, (2018)CASH: compiler assisted hardware design for improving DRAM energy efficiency in CNN inference., , , , , and . MEMSYS, page 396-407. ACM, (2019)Gesture-SNN: Co-optimizing accuracy, latency and energy of SNNs for neuromorphic vision sensors., , , , , and . ISLPED, page 1-6. IEEE, (2021)Morphable Convolutional Neural Network for Biomedical Image Segmentation., , , , , , and . DATE, page 1522-1525. IEEE, (2021)Predicting Protein-Ligand Docking Structure with Graph Neural Network., , , , , , , , and . J. Chem. Inf. Model., 62 (12): 2923-2932 (2022)Guiding Conventional Protein-Ligand Docking Software with Convolutional Neural Networks., , , , , , , and . J. Chem. Inf. Model., 60 (10): 4594-4602 (2020)