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  • 1 min read

Deep learning based super resolution, without using a GAN.

Super-resolution is a technique that enhances the quality and detail of low-resolution images, effectively transforming them into higher-resolution versions. Traditional upscaling methods often result in images lacking fine details and may introduce defects or compression artifacts. Deep learning approaches, particularly those utilizing Generative Adversarial Networks (GANs), have shown significant improvements in this area. However, training GANs can be complex and resource-intensive.

  • 1 min read

Random forests - a free lunch that’s not cursed.

Random forests are a powerful machine learning technique that combines multiple decision trees to enhance predictive accuracy and control overfitting. By aggregating the results of various trees, random forests mitigate the risk of individual trees capturing noise from the training data, leading to more robust and reliable models.