PinnedWhy Most Published Research Findings Are FalseThere is growing concern that the majority of research findings that have been published are inaccurate. The chance that a research…Jan 29, 20234Jan 29, 20234
Understanding Independent and Identically Distributed (i.i.d.) Data in StatisticsIn the field of statistics, “Independent and Identically Distributed” (i.i.d.) is a fundamental concept that underpins many statistical…Jul 28, 2023Jul 28, 2023
Introducing Markov Chain Monte Carlo: A Powerful Tool for Simulations and BeyondIn the world of statistical simulations and data analysis, Markov Chain Monte Carlo (MCMC) has emerged as a powerful and versatile…Jul 24, 2023Jul 24, 2023
Introduction to Gibbs SamplingGibbs sampling is a Markov Chain Monte Carlo (MCMC) technique used for statistical inference and sampling from complex probability…Jul 24, 2023Jul 24, 2023
Understanding Maximum Likelihood Estimation (MLE) in Machine LearningMaximum Likelihood Estimation (MLE) is a fundamental concept in machine learning and statistics that plays a crucial role in parameter…Jul 22, 20232Jul 22, 20232
Understanding Maximum a Posteriori (MAP) Estimation in Machine LearningIn the field of machine learning, making accurate predictions from data is crucial for building effective models. One common challenge is…Jul 22, 2023Jul 22, 2023
Marginalization in Gaussian DistributionMarginalization is a fundamental operation in probability and statistics that involves integrating out or summing over a variable to obtain…Jul 21, 2023Jul 21, 2023
Sinkhorn Knopp: Unraveling Optimal Transport for Data AlignmentIn the realm of data alignment and optimal transport, the Sinkhorn Knopp algorithm has emerged as a powerful tool for solving…Jun 22, 2023Jun 22, 2023
Understanding SIMCLR: Unleashing the Power of Self-Supervised LearningIn the realm of deep learning, data is paramount. Labeled data, though valuable, can be scarce and expensive to acquire. This is where…Jun 21, 2023Jun 21, 2023
BYOL: Bootstrap Your Own Latent — A New Approach to Self-Supervised LearningSelf-supervised learning has emerged as a powerful technique for training deep neural networks without relying on manual annotations…Jun 21, 2023Jun 21, 2023
