Abstract page for arXiv paper 2511.12507: Hierarchical Frequency-Decomposition Graph Neural Networks for Road Network Representation Learning
We analyze numerically the training dynamics of deep neural networks (DNN) by using methods developed in statistical physics of glassy systems. The two main issues we address are (1) the complexity
High Resolution Net (HRNet) is a state of the art neural network for human pose estimation - an image processing task which finds the
Brain-inspired spiking neural networks (SNNs) have recently drawn more and more attention due to their event-driven and energy-efficient characteristics. The integration of storage and computation paradigm on neuromorphic hardwares makes SNNs much different from Deep Neural Networks (DNNs). In this paper, we argue that SNNs may not benefit from the weight-sharing mechanism, which can effectively reduce parameters and improve inference efficiency in DNNs, in some hardwares, and assume that an SNN with unshar
FAME shows how formal neural-network explanations can scale by using abstract verification to prune the search space before exact refinement
# Recurrent Neural Networks in Tensorflow III Tue 15 November 2016 ## Task In this post, we’ll use Tensorflow to construct an RNN that operates on input sequences of variable lengths. We’ll use this RNN to classify bloggers by age bracket and gender using sentence-long writing samples. One time step will represent a single word, with the complete input sequence representing a single sentence. The challenge is to build a model that can classify multiple sentences of different lengths at the same time
Make the neural network more lenient to solve complex tasks, understand the concept, role, and all the 7 types of activation functions in neural networks
Rigorous treatment of GNNs: message passing framework, GCN spectral derivation, GAT attention, GraphSAGE sampling, WL expressivity limits, over-smoothing, and applications.
Society Leadership Founding Generation Fellowship Guidelines Merit Awards Award Recipients ICIS Listserv Congress 2026 Panama City Abstract Submissions Destination Pre-Congress Workshops Presentation Guidelines Program Registration Review Panels Speakers Sponsor/Exhibit Travel Awards Past Congresses Events & Initiatives Google Translate disclaimer Uncovering cognition in young infants using deep neural networks and awake fMRI Anyone who interacts with a young infant may find themselves wondering
Skip to content TheLinuxCode Software Menu Toggle Distros Menu Toggle SysAdmin Menu Toggle Residential Proxies Residential Proxies TheLinuxCode Main Menu Menu Optimization Rule in Deep Neural Networks: Practical Guide, 2026 Edition Leave a Comment / By Linux Code / January 8, 2026 Why I care about the optimization rule I build and ship deep learning systems weekly, and the single thing that decides whether a model trains in 2 hours or 2 weeks is the optimization rule. I treat the optimization rule like engi