Check this newly published article "Symmetry and Skewness in Weibull Modeling: Optimal Grouping for Parameter Estimation in Fertilizer Granule Strength" at brnw.ch/21x2reE Authors: Wojciech Przystupa et al. #mdpisymmetry #maximumlikelihoodestimation #skewness @UPLublin

Learning faithful representations of quantum states is crucial to fully characterizing the variety of #manybodystates created on quantum processors. While various tomographic methods such as #classicalshadow and #MPStomography have shown promise in characterizing a wide class of quantum states, they face unique limitations in detecting topologically ordered two-dimensional states. To address this problem, we implement and study a heuristic tomographic method that combines variational optimization on tensor networks with randomized measurement techniques. Using this approach, we demonstrate its ability to learn the ground state of the #surfacecodeHamiltonian as well as an experimentally realizable quantum spin liquid state. In particular, we perform numerical experiments using MPS ansätze and systematically investigate the sample complexity required to achieve high fidelities for systems of sizes up to 48 qubits. In addition, we provide theoretical insights into the scaling of our learning algorithm by analyzing the statistical properties of #maximumlikelihoodestimation. Notably, our method is sample-efficient and experimentally friendly, only requiring snapshots of the quantum state measured randomly in the X or Z bases. Using this subset of measurements, our approach can effectively learn any real pure states represented by #tensornetworks, and we rigorously prove that random-XZ measurements are tomographically complete for such states.

✅#MaximumLikelihoodEstimation is a powerful method for estimating parameters of a statistical model by maximizing likelihood function which represents probability of observing data given model & its parameters

Read #NewPaper: "Optimal Estimation of Quantum Coherence by Bell State Measurement: A Case Study" by Yuan Yuan et al. See more details at: mdpi.com/1099-4300/25/10/145… #quantumcoherence #Bellstatemeasurement #maximumlikelihoodestimation #quantummeasurement

The simplicity of Statistical Language Models is based on #MarkovAssumption and #MaximumLikelihoodEstimation. In 15 minutes you can learn how it works in today's #ise2022 lecture #NLP youtube.com/watch?v=gK4GpXhO…

Cash App Labs Modifies the Very Deep VAE to Achieve a 2.6x Speedup and 20x Memory Reduction | bit.ly/3iSwues #AI #ML #ArtificialIntelligence #MachineLearning #MaximumLikelihoodEstimation #VariationalAutoencoder #DeepNeuralNetwork

#MaximumLikelihoodEstimation #MLE is one of the most important methods for parameter estimation in modern social sciences. Learn the basic idea of MLE on @SusumuShikano two-day course bit.ly/2mmSdRY at #ecprws20 in Bamberg 🇩🇪 🖱️ Now registering! Deadline 12 December

For which parameter value the observed data have the biggest probability? Learn the answer to that by clicking the link: buff.ly/2JapJVu #MaximumLikelihoodEstimation #Calculus #Distribution #Mathematics #ArtificialIntelligence

We can combine #MaximumLikelihoodEstimation with #supervisedlearning. Meaning introducing the ground truth into our formulation. Then we can derive the final #Error Function that we would like to minimize. Enjoy down below: #MachineLearning #Statistics

#Statistics #MachineLearning: The estimates of #regression coefficients in #MaximumLikelihoodEstimation with a #LASSO penalty are often zero