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You are here		www.depthfirstlearning.com Variational Inference with Normalizing Flows · Depth First Learning
\|	\|	kyunghyuncho.me Stochastic variational inference for low-rank stochastic block models, or how i re-discovered SBM unnecessarily - Kyunghyun Cho	2.4 parsecs Travel
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\|	\|	jxmo.io Introduction to variational autoencoders - Jack Morris A primer on variational autoencoders (VAEs) culminating in a PyTorch implementation of a VAE with discrete latents.	0.7 parsecs Travel
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\|	\|	yang-song.net Generative Modeling by Estimating Gradients of the Data Distribution \| Yang Song This blog post focuses on a promising new direction for generative modeling. We can learn score functions (gradients of log probability density functions) on a large number of noise-perturbed data distributions, then generate samples with Langevin-type sampling. The resulting generative models, often called score-based generative models, has several important advantages over existing model families: GAN-level sample quality without adversarial training, flexible model architectures, exact log-likelihood ...	1.2 parsecs Travel
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\|	\|	haifengl.wordpress.com LLM \| Haifeng's Random Walk Generative artificial intelligence (GenAI), especially ChatGPT, captures everyone's attention. The transformerbased large language models (LLMs), trained on a vast quantity of unlabeled data at scale, demonstrate the ability to generalize to many different tasks. To understand why LLMs are so powerful, we will deep dive into how they work in this post. LLM Evolutionary Tree...	13.9 parsecs Travel
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