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blog.evjang.com | ||
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yang-song.net
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| | | | | 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 ... | |
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dennybritz.com
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| | | | | Deep Learning is such a fast-moving field and the huge number of research papers and ideas can be overwhelming. | |
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evjang.com
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| | | | | This blog post outlines a key engineering principle I've come to believe strongly in for building general AI systems with deep learning. This principle guides my present-day research tastes and day-to-day design choices in building large-scale, general-purpose ML systems. Discoveries around Neural Scaling Laws, unsupervised pretraining on Internet-scale datasets, and other work on Foundation Models have pointed to a simple yet exciting narrative for making progress in Machine Learning: Large amounts of d... | |
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haifengl.wordpress.com
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| | | 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... | ||
