Taesu Kim

7 Abonné

artificial intelligence deep learning neural networks machine learning meta-learning deep neural networks interpretable ml network pruning few-shot learning computer vision debugging neural network music timbre tranfer timbretron generative model flow based generative model video translation video synthesis video-to-video synthesis adaptation speech enhancement blind source separation speech separation verifiable computing decentralized computation ethereum block chain explainable ai speech audio iclr

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Taesu Kim

Présentations

PR-043: HyperNetworks

Issues in AI product development and practices in audio applications

PR12-094: Model-Agnostic Meta-Learning for fast adaptation of deep networks

PR12-151 The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

PR12-165 Few-Shot Adversarial Learning of Realistic Neural Talking Head Models

PR12-179 M3D-GAN: Multi-Modal Multi-Domain Translation with Universal Attention

PR12-193 NISP: Pruning Networks using Neural Importance Score Propagation

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Understanding deep learning requires rethinking generalization (2017) 2 2(2)