GitHub

Detection of Accounting Anomalies using Deep Autoencoder Neural Networks

An interactive lab we prepared for NVIDIA's GPU Technology Conference 2018 that will walk you through the detection of accounting anomalies using deep autoencoder neural networks. The the lab content ...
InfoWorld

10 tips for getting better R code from your AI coding agent

With the proper setup and guidance, you can have Claude Code, Codex, Posit Assistant, and other coding agents writing R code ...
The Hacker News

AutoJack Attack Lets One Web Page Hijack AI Agent for Host Code Execution

Microsoft details AutoJack exploit chain targeting AutoGen Studio MCP WebSocket in pre-release builds, enabling ...
Frontiers

Beyond the single neuron: computational principles of distributed neural coding in the age of large-scale recordings

You will be redirected to our submission process. Neural coding is the fundamental language of the brain, the set of rules by which stimulus features and internal states are transformed into ...
Nature

Streamflow prediction using an integrated methodology based on convolutional neural network and long short-term memory networks

Long short-term memory Recurrent neural network (RNN) are powerful and robust type of artificial neural networks that uses existing time-series data to predict the future data over a specified length ...
GitHub

message-passing-neural-network

Melty Molecule is a molecular property prediction system that leverages graph neural networks to predict melting points of chemical compounds. The model uses a hybrid architecture combining Principal ...
Frontiers

Deep learning assisted modeling of Li-ion transport in SEI: a graph neural network based study

In the second stage of this work, the Li-ion diffusion information generated from the DFT–NEB calculations is used to develop a graph neural network (GNN)-assisted predictive model for estimating ...