Decoupling and predicting natural gas deviation factor using machine learning methods
Basic datasetThe foundational Z-factor data for developing the machine learning models were sourced from gas wells of the Jurassic Shaximiao...
Learning
LASR: A Novel Machine Learning Approach to Symbolic Regression Using Large Language Models
Symbolic regression is an advanced computational method to find mathematical equations that best explain a dataset. Unlike traditional regression, which...
The ethical imperatives of implementing learning technologies –
Learning technologies are changing the game, but it’s crucial to navigate their use with care. Dr Ajit Kumar Kar breaks...
Self-inspired learning for denoising live-cell super-resolution microscopy
Schermelleh, L. et al. Super-resolution microscopy demystified. Nat. Cell Biol. 21, 72–84 (2019).Article CAS PubMed Google Scholar Schermelleh, L. et...
DPAdapter: A New Technique Designed to Amplify the Model Performance of Differentially Private Machine Learning DPML Algorithms by Enhancing Parameter Robustness
Privacy in machine learning is critical, especially when models are trained on sensitive data. Differential privacy (DP) offers a framework...
Hands-On Imitation Learning: From Behavior Cloning to Multi-Modal Imitation Learning | by Yasin Yousif | Sep, 2024
An overview of the most prominent methods in imitation learning while testing on a grid environmentPhoto by Possessed Photography on...
