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cuDNN: Efficient Primitives for Deep Learning., , , , , , and . CoRR, (2014)Fully Convolutional Multi-Class Multiple Instance Learning., , , and . ICLR (Workshop), (2015)Caffe, , , , , , , and . Proceedings of the 22nd ACM international conference on Multimedia, ACM, (November 2014)Learning Rich Image Representation with Deep Layer Aggregation., , , and . ICLR (Workshop), OpenReview.net, (2018)It Is Likely That Your Loss Should be a Likelihood., , and . CoRR, (2020)Loss is its own Reward: Self-Supervision for Reinforcement Learning., , , and . ICLR (Workshop), OpenReview.net, (2017)Infinite Mixture Prototypes for Few-shot Learning., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 232-241. PMLR, (2019)Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks., , , , and . CoRR, (2021)Perceiver IO: A General Architecture for Structured Inputs & Outputs., , , , , , , , , and 5 other author(s). ICLR, OpenReview.net, (2022)Exploring Simple and Transferable Recognition-Aware Image Processing., , , , , , and . IEEE Trans. Pattern Anal. Mach. Intell., 45 (3): 3032-3046 (March 2023)