'Underwater' car trade-ins are at a 4-year high: What that means when buying a new vehicle 'I like not-working better': A ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

Understand the merits of large language models vs. small language models, and why knowledge graphs are the missing piece in ...

Abstract: In the field of time series prediction, runoff prediction is a critical subfield. Accurate runoff forecasting is essential for optimizing water resource allocation and mitigating flood risks ...

This project contains implementations of simple neural network models, including training scripts for PyTorch and Lightning frameworks. The goal is to provide a modular, easy-to-understand codebase ...

This repository contains a time series forecasting project using the Google Play Store dataset. It systematically compares RNN, LSTM, and GRU models, optimized via Keras Tuner, to predict future app ...

Researchers unveil OneFlip, a Rowhammer-based attack that flips a single bit in neural network weights to stealthily backdoor AI systems without degrading performance. Autonomous vehicles and many ...

Capital One was already a major credit card issuer. Now it’s also got a payment network presence. The credit card giant is also a bank, even if it’s not yet done a great deal of business-building on ...

The Trump administration is seeking a refresh in how the federal government designs public-facing services. President Donald Trump launched a new National Design Studio within the White House, as part ...

This video is an overall package to understand Dropout in Neural Network and then implement it in Python from scratch. Dropout in Neural Network is a regularization technique in Deep Learning to ...