Scientific Research Publishing

Spatiotemporal Evolution Patterns and Intelligent Forecasting of Passenger Flow in Megacity High-Speed Rail Hubs: A Case Study of Guangzhou South Railway Station ()

Spatiotemporal Evolution Patterns and Intelligent Forecasting of Passenger Flow in Megacity High-Speed Rail Hubs: A Case ...
eLife

Retrosplenial cortex enables context-dependent goal-directed sensorimotor transformation

This important study combines optogenetic manipulations and wide-field imaging to show that the retrosplenial cortex controls behavioral responses to whisker deflection in a context-dependent manner.
C&EN

Machine Learning-Powered Forecasting of Hydrogen Solubility in Brines for Geological Storage: The Role of Pressure, Temperature, Salinity, and Salt Type

(*, **) Although the paper reports this low R 2 value, it is likely a typographical error. Thus, unlike prior studies, often constrained by modest sample sizes and a ...
Search Engine Land

Image optimization for SEO: A complete guide for beginners

You might be staring at your SEO checklist in disbelief right now. Rightfully so. You’re already optimized the metadata, headers, internal links, copy, and even done some technical setup for every ...
GitHub

An AutoML framework for classical machine learning algorithms, automating model selection and hyperparameter tuning through Bayesian optimization, portfolio-based meta-learning ...

Start a Ray head node Connect and start Ray worker nodes via SSH Activate virtual environments and configure PYTHONPATH on all nodes 📌 Before running the script, ensure passwordless SSH access from ...
IEEE

Automated Class Imbalance Learning via Few-shot Multi-Objective Bayesian Optimization with Deep Kernel Gaussian Processes

Abstract: Automated Class Imbalance Learning (AutoCIL) is an emerging paradigm that leverages Combined Algorithm Selection and Hyperparameter Optimization (CASH) to automate the configuration of ...
IEEE

Optimizing Hyperparameters in Meta-learning for Enhanced Image Classification

Abstract: This paper investigates the significance of hyperparameter optimization in meta-learning for image classification tasks. Despite advancements in deep learning, real-time image classification ...
GitHub

[FR] Native Bayesian Hyperparameter Optimization Integration

Add native support for Bayesian hyperparameter optimization directly within MLflow, eliminating the need for external libraries like Optuna or Hyperopt. This feature would provide a deeply integrated ...