LabFab
Exploring math, physics, machine learning, and finance insights.
Category investing portfolio management
Last week I came across a fascinating research paper, “Tail Protection for Long Investors: Trend Convexity at Work” by researchers from Capital Fund Management. As someone who’s weathered multiple market...
Category trading strategies
Last week I came across a fascinating research paper, “Tail Protection for Long Investors: Trend Convexity at Work” by researchers from Capital Fund Management. As someone who’s weathered multiple market...
Category risk management
Last week I came across a fascinating research paper, “Tail Protection for Long Investors: Trend Convexity at Work” by researchers from Capital Fund Management. As someone who’s weathered multiple market...
Category machine learning
Graph Neural Networks (GNNs) represent a fundamental paradigm shift in deep learning, extending the remarkable success of neural networks from Euclidean domains like images and sequences to the irregular, non-Euclidean...
Gradient descent is the workhorse of modern machine learning, but vanilla gradient descent often struggles with challenges like saddle points, ravines, and local minima. Momentum-based methods address these limitations through...
Category optimization algorithms
Gradient descent is the workhorse of modern machine learning, but vanilla gradient descent often struggles with challenges like saddle points, ravines, and local minima. Momentum-based methods address these limitations through...
Category deep learning
Graph Neural Networks (GNNs) represent a fundamental paradigm shift in deep learning, extending the remarkable success of neural networks from Euclidean domains like images and sequences to the irregular, non-Euclidean...
Gradient descent is the workhorse of modern machine learning, but vanilla gradient descent often struggles with challenges like saddle points, ravines, and local minima. Momentum-based methods address these limitations through...
Category quantum physics
Richard Feynman’s path integral formulation stands as one of the most elegant and profound reformulations of quantum mechanics ever conceived. Unlike the traditional Schrödinger equation approach, path integrals offer an...
Imagine zooming into the fabric of spacetime itself, magnifying it by a factor of $10^{35}$—from human scales down to the Planck length of approximately $1.6 \times 10^{-35}$ meters. What would...
Category theoretical physics
The concept of a connection stands as one of the most beautiful unifications in mathematical physics, bridging the abstract world of differential geometry with the concrete phenomena of gauge fields...
Richard Feynman’s path integral formulation stands as one of the most elegant and profound reformulations of quantum mechanics ever conceived. Unlike the traditional Schrödinger equation approach, path integrals offer an...
Imagine zooming into the fabric of spacetime itself, magnifying it by a factor of $10^{35}$—from human scales down to the Planck length of approximately $1.6 \times 10^{-35}$ meters. What would...
Category mathematics
Richard Feynman’s path integral formulation stands as one of the most elegant and profound reformulations of quantum mechanics ever conceived. Unlike the traditional Schrödinger equation approach, path integrals offer an...
Imagine zooming into the fabric of spacetime itself, magnifying it by a factor of $10^{35}$—from human scales down to the Planck length of approximately $1.6 \times 10^{-35}$ meters. What would...
Category mathematical physics
The concept of a connection stands as one of the most beautiful unifications in mathematical physics, bridging the abstract world of differential geometry with the concrete phenomena of gauge fields...
Category particle physics
The concept of a connection stands as one of the most beautiful unifications in mathematical physics, bridging the abstract world of differential geometry with the concrete phenomena of gauge fields...
Category graph theory
Graph Neural Networks (GNNs) represent a fundamental paradigm shift in deep learning, extending the remarkable success of neural networks from Euclidean domains like images and sequences to the irregular, non-Euclidean...
Category artificial intelligence
Large Language Models present us with a fascinating paradox. They can write poetry that moves us to tears, engage in sophisticated philosophical discussions, and even generate code that solves complex...
Category mathematical reasoning
Large Language Models present us with a fascinating paradox. They can write poetry that moves us to tears, engage in sophisticated philosophical discussions, and even generate code that solves complex...
Category computational logic
Large Language Models present us with a fascinating paradox. They can write poetry that moves us to tears, engage in sophisticated philosophical discussions, and even generate code that solves complex...
