Published on: 2025-06-24 23:50:16
Warning: Math, Handwaving I spent a lot of time doodling in middle school in lieu of whatever it is middle schoolers are supposed to be doing. Somewhere between the Cool S’s and Penrose triangles I stumbled upon a neat way to fill up graph paper by repeatedly combining and copying squares. I suspected there was more to the doodle but wasn’t quite sure how to analyze it. Deciding to delegate to a future version of me that knows more math, I put it up on the wall behind my desk where it has follo
Keywords: begin bmatrix end iteration overrightarrow
Find related items on AmazonPublished on: 2025-06-26 15:50:16
Content Warning: Math, Handwaving I spent a lot of time doodling in middle school in lieu of whatever it is middle schoolers are supposed to be doing. Somewhere between the Cool S’s and Penrose triangles I stumbled upon a neat way to fill up graph paper by repeatedly combining and copying squares. I suspected there was more to the doodle but wasn’t quite sure how to analyze it. Deciding to delegate to a future version of me that knows more math, I put it up on the wall behind my desk where it h
Keywords: begin bmatrix end iteration overrightarrow
Find related items on AmazonPublished on: 2025-07-04 07:39:31
Fahmatrix Fahmatrix is a lightweight, modern Java library for working with tabular data, inspired by Python's Pandas and rooted in the idea of making data understanding (fahm) easy on the JVM. 🚀 Intuitive API for tabular data 📄 Easy CSV reading and previewing 🔍 Row filtering and column selection 📊 Aggregations, grouping, and sorting (coming soon) 🧩 No external dependencies (for now) 🔧 Installation 📦 Using GitHub Releases Visit Releases and download the latest JAR file. Include it manua
Keywords: csv data dataframe fahmatrix java
Find related items on AmazonPublished on: 2025-07-12 00:59:39
Apple’s Machine Learning team, in collaboration with researchers from Nanjing University and The Hong Kong University of Science and Technology, has announced an interesting 3D AI model called Matrix3D. This so-called Large Photogrammetry Model is able to reconstruct 3D objects and scenes from just a few 2D photos, but with a big difference from current pipelines. Here’s why this is a big deal. First things first: photogrammetry. It uses photographs to make measurements in order to create 3D m
Keywords: 3d interesting matrix3d model researchers
Find related items on AmazonPublished on: 2025-08-02 03:18:52
In numerous applications of machine learning, Hessians and Jacobians exhibit sparsity, a property that can be leveraged to vastly accelerate their computation. While the usage of automatic differentiation in machine learning is ubiquitous, automatic sparse differentiation (ASD) remains largely unknown. This post introduces ASD, explaining its key components and their roles in the computation of both sparse Jacobians and Hessians. We conclude with a practical demonstration showcasing the performa
Keywords: ad jacobian mathbf matrix sparsity
Find related items on AmazonPublished on: 2025-08-18 10:42:48
Introduction This post details my recent efforts to write an optimized matrix multiplication kernel in CUDA using tensor cores on a NVIDIA Tesla T4 GPU. The goal is to compute $D = \alpha * A * B + \beta * C$, as fast as possible. In this equation $D,A,B$ and $C$ are large matrices full of half precision floating point numbers, and $\alpha$, $\beta$ are constants. This problem is usually referred to as a Half-precision Generalized Matrix Multiply, or HGEMM for short. Tensor Cores are specializ
Keywords: data kernel matrix memory shared
Find related items on AmazonPublished on: 2025-08-18 15:42:48
Introduction This post details my recent efforts to write an optimized matrix multiplication kernel in CUDA using tensor cores on a NVIDIA Tesla T4 GPU. The goal is to compute $D = \alpha * A * B + \beta * C$, as fast as possible. In this equation $D,A,B$ and $C$ are large matrices full of half precision floating point numbers, and $\alpha$, $\beta$ are constants. This problem is usually referred to as a Half-precision Generalized Matrix Multiply, or HGEMM for short. Tensor Cores are specializ
Keywords: data kernel matrix memory shared
Find related items on AmazonPublished on: 2025-09-15 22:28:50
On Monday 7th of April 2025 at 7am UTC, we will migrate the Matrix.org homeserver's authentication system over to MAS (Matrix Authentication Service) in order to benefit from Next-generation authentication. The migration will involve up to one hour of downtime. MSC3861 (Next-generation auth for Matrix, based on OAuth 2.0/OIDC) and its dependent MSCs have progressed sufficiently that the Foundation is confident in MAS and the new next-generation auth APIs.Specifically, all the MSCs are now in o
Keywords: account authentication generation matrix new
Find related items on AmazonPublished on: 2025-09-30 23:06:36
Date Tue 07 February 2023 Tags Programming Given a transform \(T\) and a point x, we can find the transformed point with \(T * x\). But what if we want to smoothly interpolate \(T\) so it moves \(x\) along the path from its initial position to its position transformed by \(T\)? What we want to find is the point \(x\) at time \(t\): \(x(t) = T(t) * x(0)\) where \(x(0)\) is the point’s initial position, and \(T(t)\) is the transform at time \(t\). Since we have only a single transform \(T\), w
Keywords: log logarithm matrix point transform
Find related items on AmazonPublished on: 2025-11-02 00:41:14
Writing an LLM from scratch, part 8 -- trainable self-attention This is the eighth post in my trek through Sebastian Raschka's book "Build a Large Language Model (from Scratch)". I'm blogging about bits that grab my interest, and things I had to rack my brains over, as a way to get things straight in my own head -- and perhaps to help anyone else that is working through it too. It's been almost a month since my last update -- and if you were suspecting that I was blogging about blogging and spe
Keywords: attention input matrix space token
Find related items on AmazonPublished on: 2025-11-10 17:03:59
Markov Chains Explained Visually By Victor Powell with text by Lewis Lehe Markov chains, named after Andrey Markov, are mathematical systems that hop from one "state" (a situation or set of values) to another. For example, if you made a Markov chain model of a baby's behavior, you might include "playing," "eating", "sleeping," and "crying" as states, which together with other behaviors could form a 'state space': a list of all possible states. In addition, on top of the state space, a Markov
Keywords: chain markov matrix state transition
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