IEEE

Deep Reinforcement Learning-Assisted Robust Cubature Kalman Filter for Power System Dynamic State Estimation With Multi-Rate Measurements

Abstract: The coexistence of high-frequency phasor measurement units (PMUs) and conventional SCADA systems raises the challenge of heterogenous-source and multi-rate measurements which significantly ...
Deep Learning with Yacine on MSN

AdamW optimizer from scratch in Python – step-by-step tutorial

Build the AdamW optimizer from scratch in Python. Learn how it improves training stability and generalization in deep ...
InfoWorld

Which development platforms and tools should you learn now?

For software developers, choosing which technologies and skills to master next has never been more difficult. Experts offer ...
Deep Learning with Yacine on MSN

Adadelta optimizer explained – Python tutorial for beginners & pros

Learn how to implement the Adadelta optimization algorithm from scratch in Python. This tutorial explains the math behind Adadelta, why it was introduced as an improvement over Adagrad, and guides you ...
marktechpost

How to Design Transactional Agentic AI Systems with LangGraph Using Two-Phase Commit, Human Interrupts, and Safe Rollbacks

In this tutorial, we implement an agentic AI pattern using LangGraph that treats reasoning and action as a transactional workflow rather than a single-shot decision. We model a two-phase commit system ...
IEEE

Data-Driven Motion Planning: A Survey on Deep Neural Networks, Reinforcement Learning, and Large Language Model Approaches

Abstract: Motion planning is a fundamental challenge in robotics, involving the creation of trajectories from start to goal states while meeting constraints like collision avoidance and joint limits.