Visualizing Live Collision Risk in London: A Machine Learning Approach
As someone who’s passionate about making cities safer, I wanted to explore the relationship between collisions and location in London. […]
Machine Learning
Modeling Attention as Resonance Frequency: A New Perspective
Have you ever wondered if there’s more to attention mechanisms than just static weighting? Traditional attention models use softmax over
Detecting Vulnerabilities in LLMs: A New Project
As a machine learning enthusiast, I’ve always been fascinated by the potential of large language models (LLMs) to revolutionize the
Unlocking Backpropagation with Triton BWD: A Breakthrough in GPU Kernel Code
If you’ve ever worked with OpenAI’s Triton language, you know how powerful it can be for writing GPU kernel code.
Why Mamba Architecture Might Not Be as Popular in Research
Have you ever wondered why Mamba architecture isn’t as widely used in research as other models? As someone interested in
Drift Benchmark Report: PKBoost vs LightGBM vs XGBoost
If you’re working with machine learning models, you know how tough it can be to deal with drift. That’s when
Feature Selection in High-Dimensional Linear Regression: Is Correlation Enough?
When working with a large number of potential independent variables, feature selection is crucial to prevent overfitting and improve model
Uncovering the FER2013 Dataset: A Machine Learning Enigma
I’ve been exploring the FER2013 dataset, and I have to say, it’s a fascinating piece of work. For those who