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This chapter presents recent papers for using FPGAs (Field Programmable Gate Arrays) for Deep Learning. FPGAs can roughly be seen as a Software-configurable Hardware, i.e you in some cases get close to dedicated hardware speed (although typically at lower clock frequency than chips, but typically with strong on-FPGA parallelism), this can be a potential good fit for e.g. Convolutional Neural Netwo
Deep Learning with Generative and Generative Adverserial Networks – ICLR 2017 Discoveries The 5th International Conference on Learning Representation (ICLR 2017) is coming to Toulon, France (April 24-26 2017). This blog post gives an overview of Deep Learning with Generative and Adverserial Networks related papers submitted to ICLR 2017, see underneath for the list of papers. Want to learn about t
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