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One deep music representation to rule them all? A comparative analysis of different representation learning strategies., , , and . Neural Comput. Appl., 32 (4): 1067-1093 (2020)Make Some Noise. Unleashing the Power of Convolutional Neural Networks for Profiled Side-channel Analysis., , , , and . IACR Trans. Cryptogr. Hardw. Embed. Syst., 2019 (3): 148-179 (2019)FreGrad: Lightweight and Fast Frequency-aware Diffusion Vocoder., , , , and . CoRR, (2024)Butter Lyrics Over Hominy Grit: Comparing Audio and Psychology-Based Text Features in MIR Tasks., , , , and . ISMIR, page 861-868. (2020)Effective Network Compression Using Simulation-Guided Iterative Pruning., , , , and . CoRR, (2019)Generative Autoregressive Networks for 3D Dancing Move Synthesis from Music., , , and . CoRR, (2019)The power of deep without going deep? A study of HDPGMM music representation learning., and . ISMIR, page 116-124. (2022)Single and Multi Column Neural Networks for Content-based Music Genre Recognition., , , and . MediaEval, volume 1984 of CEUR Workshop Proceedings, CEUR-WS.org, (2017)Dissecting 802.11ac Performance - Why You Should Turn Off MU-MIMO., , , , and . MobiSys, page 510-511. ACM, (2019)Use MU-MIMO at your own risk - Why we don't get Gb/s Wi-Fi., , , , and . Ad Hoc Networks, (2019)