Mathematics

As the company behind Stable Diffusion, Stability AI is best recognized for developing some of the most well-known state-of-the-art AI models for a variety of applications, including language, vision, audio, 3D modeling, etc. The $1 billion...
GPT-4 has been released, and it is already in the headlines. It is the technology behind the popular ChatGPT developed by OpenAI which can generate textual information and imitate humans in question answering. After the success...

MIT Researchers Create ‘ExSum’: A Mathematical Framework To Evaluate Explanations Of Machine Learning Models And Quantify How Well People Understand Them

This Article Is Based On The Research Paper 'EXSUM: From Local Explanations to Model Understanding'. All Credit For This Research Goes To The Researchers...

Understanding Goodhart’s Law Metrics and Mathematics Behind The Process

This article is based on OpenAI's Post 'Measuring Goodhart’s Law'. Most credit goes to OpenAI researchers 👏👏👏 Please don't forget to join our ML...

Researchers, Including Yann Lecun, Propose ‘projUNN’: An Efficient Method For Training Deep Neural Networks With Unitary Matrices

This research summary is based on the paper 'projUNN: efficient method for training deep networks with unitary matrices' Please don't forget to join our ML...

Researchers Develop Data‑Driven Discovery of Green’s Functions With Human‑Understandable Deep Learning

This research summary is based on the paper 'Data‑driven discovery of Green’s functions with human‑understandable deep learning' Please don't forget to join our ML Subreddit Mathematicians...

UC Berkeley Researchers Introduce ‘imodels: A Python Package For Fitting Interpretable Machine Learning Models

Recent developments in machine learning have resulted in more complicated predictive models, typically at the expense of interpretability. Interpretability is frequently required, especially in...

Common Probability Distributions: Road Towards Data Science

Probability is concerned with interpreting and comprehending life's random events. Randomness and uncertainty are present in our everyday lives and every field of research,...

JuMP: An AML Based Modeling Language Embedded In Julia For Mathematical Optimization

Optimization as a fundamental technology is a universal concept that finds application in almost every discipline, including business, engineering, economics. It is defined as...

MIT Researchers Open-Sourced ‘MADDNESS’: An AI Algorithm That Speeds Up Machine Learning Using Approximate Matrix Multiplication (AMM)

Matrix multiplication is one of the essential operations in machine learning (ML). However, these operations are extensively computationally costly due to the extensive use...

Cornell University and NTT Research Introduce Physical Neural Networks (PNNs): A Universal Framework that Leverages a Backpropagation Algorithm for Arbitrary Physical Systems

DNNs (Deep neural networks) have proven to be of great use in solving various complex problems in image and speech recognition and NLP. DDNs...

Researchers from UC Berkeley and CMU Introduce a Task-Agnostic Reinforcement Learning (RL) Method to Auto-Tune Simulations to the Real World

Applying Deep Learning techniques to complex control tasks depends on simulations before transferring models to the real world. However, there is a challenging “reality...

Optimizers in Keras Part – 1

You have heard of an optimization technique named Gradient Descent. Now, suppose you are dealing with a massive dataset having one million data points....

Understanding Neuromorphic Computing: The Next Generation of AI

Neuromorphic computing, as the name suggests, uses a model that’s inspired by the workings of the brain. The brain makes an appealing model for...

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