John Resig OCR and Neural Nets in JavaScript A pretty amazing piece of JavaScript dropped yesterday and it’s going to take a little bit to digest it all. It’s a GreaseMonkey script, written by ‘ Shaun Friedle ‘, that automatically solves captchas provided by the site Megaupload . There’s a demo online if you wish to give it a spin. Now, the captchas provided by the site aren’t very “hard” to solve (in fact, they’re downright bad – some examples are below): But there are many interesting

When the brain's connections go into overdrive, the effects ripple through everything, perception, mood, attention, memory, and behavior.

Abstract page for arXiv paper 2106.00393: Relational Reasoning Networks

DAG-Explainer targets data-aware global explanations for pretrained GNNs, jointly optimizing model faithfulness, distribution compliance, and class discrimination. It formalizes the NP-hard…

Talk:Deep belief networks From Scholarpedia (Difference between revisions) Jump to: navigation , search Revision as of 12:46, 5 May 2009 ( view source ) m (Reviewer A:) ← Older edit Latest revision as of 13:52, 5 May 2009 ( view source ) m (Reviewer A:) Line 15: Line 15: ---------------------- ---------------------- − This is an excellent, timely, and necessary contribution to Scholarpedia. I would certainly not shorten it, and I agree with the comments from the second review in this respect, i.e., I

最新論文・ユースケース・イベントレポートなどのお役立ちブログの「Convolutional Neural Network (CNN) for Time Series Classification」ページです。DXプロジェクトをけん引する皆様に向けて「AI社会実装

Keras documentation: Approximating non-Function Mappings with Mixture Density Networks

Explores whether constraining most model weights to zero during training produces human-understandable circuits and disentangled representations, rather than attempting to reverse-engineer dense models after training.

微软嵌入式学习库）文章合集 ♬♬♬♬♬ ✍ 《Neural Networks and Deep Learning》读书笔记：最简单的识别MNIST的神经网络程序(1) ✍ 《Neural Networks and Deep Learning》读书笔记：最简单的识别MNIST的神经网络程序(2) ✍ 《Neural Networks and Deep Learning》读书笔记：反向传播的4个基本方程(1) ✍ 用人话解

ISCA Archive Interspeech 2025 ISCA Archive Interspeech 2025 “KAN you hear me?” Exploring Kolmogorov-Arnold Networks for Spoken Language Understanding Alkis Koudounas, Moreno La Quatra, Eliana Pastor, Sabato Marco Siniscalchi, Elena Baralis Kolmogorov-Arnold Networks (KANs) have recently emerged as a promising alternative to traditional neural architectures, yet their application to speech processing remains under explored. This work presents the first investigation of KANs for Spoken Language