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francisbach.com | ||
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fa.bianp.net
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| | | | | The Langevin algorithm is a simple and powerful method to sample from a probability distribution. It's a key ingredient of some machine learning methods such as diffusion models and differentially private learning. In this post, I'll derive a simple convergence analysis of this method in the special case when the ... | |
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windowsontheory.org
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| | | | | Previous post: ML theory with bad drawings Next post: What do neural networks learn and when do they learn it, see also all seminar posts and course webpage. Lecture video (starts in slide 2 since I hit record button 30 seconds too late - sorry!) - slides (pdf) - slides (Powerpoint with ink and animation)... | |
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programmathically.com
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| | | | | Sharing is caringTweetIn this post, we develop an understanding of why gradients can vanish or explode when training deep neural networks. Furthermore, we look at some strategies for avoiding exploding and vanishing gradients. The vanishing gradient problem describes a situation encountered in the training of neural networks where the gradients used to update the weights [] | |
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www.preposterousuniverse.com
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| | | [AI summary] This article is a collection of discussions and perspectives on the nature of consciousness, focusing on whether it is an emergent property of complex systems. It touches on various viewpoints from different contributors, including philosophical, scientific, and even speculative theories. The discussion includes references to the role of quantum mechanics, the relationship between consciousness and the physical world, and the challenges in defining and measuring consciousness. The article also mentions the work of researchers like Sandro Sozzo and others who explore the intersection of consciousness and quantum theory. Additionally, it highlights the importance of interdisciplinary approaches in understanding consciousness, and the ongoing debat... | ||
