Two feedforward neural network models: one that could classify numbers and another that could classify clothing items

In the 1980s, neural networks hit a wall: nobody knew how to train deep models. That changed when Rumelhart, Hinton

# The Neural Geometry Series ## The World Inside Neural Networks How neural geometry will unlock understanding and control of AI Neural networks develop rich geometric structure in their activations, mirroring the structure of the world they are trained on: days of the week form circles, colors form an HSL manifold, and the tree of life appears in genomic representations. This opening post makes the case that this "neural geometry" is a crucial frontier for understanding, improving, and controlling AI mo

RNTNs are neural networks useful for natural language processing

Abstract page for arXiv paper 1805.04770: Born Again Neural Networks

Interactive neural network demo for Forex currency pair prediction. Experiment with neural network settings and observe forecasting results on exchange rate data

## Sequential Neural Networks as Automata William Merrill This work attempts to explain the types of computation that neural networks can perform by relating them to automata. We first define what it means for a real-time network with bounded precision to accept a language. A measure of network memory follows from this definition. We then characterize the classes of languages acceptable by various recurrent networks, attention, and convolutional networks. We find that LSTMs function like counter machines

NeurIPS Proceedings Search What Makes Graph Neural Networks Miscalibrated? Hans Hao-Hsun Hsu, Yuesong Shen, Christian Tomani, Daniel Cremers Advances in Neural Information Processing Systems 35 (NeurIPS 2022) Main Conference Track Abstract Given the importance of getting calibrated predictions and reliable uncertainty estimations, various post-hoc calibration methods have been developed for neural networks on standard multi-class classification tasks. However, these methods are not well suited for calibrati

latest Tutorials Basic Concepts in ZhuSuan Bayesian Neural Networks Logistic Normal Topic Models API Docs zhusuan.distributions zhusuan.framework zhusuan.variational Community Contributing ZhuSuan Docs » Bayesian Neural Networks Edit on GitHub Bayesian Neural Networks ¶ Note This tutorial assumes that readers have been familiar with ZhuSuan’s basic concepts . Recent years have seen neural networks’ powerful abilities in fitting complex transformations, with successful applications on speech

Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity December 24, 2018 Intel Neural Compute Stick 2 Filed under: Neural Information Processing , Neural Networks — Patrick Durusau @ 3:20 pm Intel Neural Compute Stick 2 (Mouser Electronics) From the webpage: Intel® Neural Compute Stick 2 is powered by the Intel™ Movidius™ X VPU to deliver industry leading performance, wattage, and power. The NEURAL COMPUTE supports OpenVINO™, a toolkit that accelerates solution development and