Analytics Insight

Best Deep Learning Books to Read in 2026

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...
IEEE

A Physics-Informed Neural Network Framework for Real-Time Model Predictive Shape Manipulation of Deformable Linear Objects

Abstract: Shape control of deformable linear objects (DLOs) is a major challenge in robotics due to their high-dimensional, nonlinear dynamics and sensitivity to boundary conditions. Existing ...
eLife

Synaptic Theory of Chunking in Working Memory

This valuable study links psychological theories of chunking with a physiological implementation based on short-term synaptic plasticity and synaptic augmentation. The theoretical derivation for ...
GitHub

Dense_NN is an EigenNET project for training dense-type neural networks implemented in C++.

A typical R and Dense_NN training workflow is described by the following images or here as a YouTube video. Dense_NN.exe is installed in the bin directory. The ...
GitHub

SPADE: Sparsity Guided Debugging for Deep Neural Networks

This repository contains the code for the paper "SPADE: Sparsity Guided Debugging for Deep Neural Networks". In this paper we improved interpretability methods by first pruning the model on the sample ...