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Analysing and Evaluating Complementarity of Multi-Modal Data Fusion in AD Diagnosis.

, , , , and . MSN, page 835-840. IEEE, (2022)

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Accelerating Spatiotemporal Supervised Training of Large-Scale Spiking Neural Networks on GPU., , , , , and . DATE, page 658-663. IEEE, (2022)Analysing and Evaluating Complementarity of Multi-Modal Data Fusion in AD Diagnosis., , , , and . MSN, page 835-840. IEEE, (2022)Faith: An Efficient Framework for Transformer Verification on GPUs., , , , , , , and . USENIX ATC, page 167-182. USENIX Association, (2022)H2Learn: High-Efficiency Learning Accelerator for High-Accuracy Spiking Neural Networks., , , , , , , , and . CoRR, (2021)Efficient tensor core-based GPU kernels for structured sparsity under reduced precision., , , , and . SC, page 78. ACM, (2021)Boosting Deep Neural Network Efficiency with Dual-Module Inference., , , , , , , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 6205-6215. PMLR, (2020)EVT: Accelerating Deep Learning Training with Epilogue Visitor Tree., , , , , , and . ASPLOS (3), page 301-316. ACM, (2024)Kernel-Centric Optimizations for Deep Neural Networks on GPGPU. University of California, Santa Barbara, USA, (2024)Batch Normalization Sampling., , , , , , and . CoRR, (2018)fuseGNN: Accelerating Graph Convolutional Neural Network Training on GPGPU., , , , , , and . ICCAD, page 60:1-60:9. IEEE, (2020)