Neural networks have been powering breakthroughs in artificial intelligence, including the large language models that are now being used in a wide range of applications, from finance, to human resources to health care. But these networks remain a black box whose inner workings engineers and scientists struggle to understand
This survey examines how tensor networks and neural networks integrate to enhance compression, multimodal fusion, and quantum circuit simulation
This explores whether the tools we use to read what neural networks are 'thinking' (probes, PCA, linear classifiers) can systematically overlook the features that actually drive computation
# st: Neural Networks From Chris Roebuck < [email protected] > Subject st: Neural Networks Date Tue, 4 Oct 2005 12:13:05 -0500 Does anyone know of ado files written for running neural network models in STATA? I can seem to find anything, but I would think this is possible, perhaps using MATA code. Otherwise, can someone email their thoughts on other software solutions for ANN. Thanks. ***************************** M. Christopher Roebuck, MBA Health Economist Manager, Predictive Modeling Research
Skip to main content itch.io Jobs clementneo published Algorithmic Explanation: A method for measuring interpretations of neural networks clementneo published a game 3 years ago Algorithmic Explanation: A method for measuring interpretations of neural networks A downloadable game. How do you make good explanations for what a neural network does? We provide a framework for analysing explanations of the behaviour of neural networks by looking at the hypothesis of how they would act on a set of given inputs. B
I created a little Shiny application to demonstrate that Neural Networks are just souped up linear models: https://lucy.shinyapps.io/neural-net-linear
Neural networks, a type of machine-learning model, are being used to help humans complete a wide variety of tasks, from predicting if someone's credit score is high enough to qualify for a loan to diagnosing whether a patient
In this article, we explore Deep Neural Networks and Gaussian Processes through comparative, theoretical, and applied lenses
# Natural Language Processing: The Evolution from Rules to Neural Networks 📅 Dec 6, 2025 ⏱️ 8 min read ## The Journey of Natural Language Processing Natural Language Processing (NLP) has undergone a remarkable transformation over the past few decades. From rule-based systems that rely on manually crafted linguistic rules to modern neural networks that learn directly from text data, NLP has evolved dramatically. This evolution mirrors broader developments in AI, reflecting our growing understanding of
Escnn, built on PyTorch, is a library that, in the spirit of Geometric Deep Learning, provides a high-level interface to designing and training group-equivariant neural networks. This post introduces important mathematical concepts, the library’s key actors