Skills Languages Python C++ [git+revsic/cpp-obfuscator, git+utilForever/RosettaStone] ML Framework Tensorflow [git+revsic/tf-glow-tts, git+revsic/tf-diffwave] PyTorch [git+revsic/torch-nansypp, git+revsic/flowmodels] Jax/Flax [git+revsic/jax-variational-diffwave] Windows Internal [git+revsic/cpp-veh-dbi]...
Variational Inference with Normalizing Flows, Rezende and Mohamed, 2015, arXiv Density Estimation using Real NVP, Dinh et al.
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Diffusion: Ho et al., 2020, arXiv:2006.11239 WaveGrad: Nanxin Chen et al.
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David Bau et al., 2020, arXiv Keyword: Generative, Adversarial learning Problem: How to manipulate specific rules encoded by a deep generative model.
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Stanislav Pidhorskyi et al., 2020, arXiv Keyword: Generative, Adversarial learning Problem: AE based approach has poor quality of output distribution.
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Hyunjik kim et al., 2019, arXiv Keyword: Bayesian, Process Problem: Underfitting of Neural Process Solution: NP + Self-Attention, Cross-Attention Benefits: Improvement of prediction accuracy, training speed, model capability.
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Marta Garnelo et al., 2018, arXiv Keyword: Bayesian, Process Problem: Data inefficiency, hard to train multiple datasets in one.
read more![[Survey, WIP] Likelihood-based Generative Models](/images/post/diffusion-survey/head_hufbb83c8cf108c6c6ea70eae717dcf6c4_291951_100x100_fill_q75_box_smart1_3.png)
