Hierarchical Clustering 3: single-link vs. complete-link
[http://bit.ly/s-link] Agglomerative clustering needs a mechanism for measuring the distance between two clusters, and we have many different ways of measuring such a distance. We explain the similarities and differences between single-link, complete-link, average-link, centroid method and
From playlist Hierarchical Clustering
Clustering 1: monothetic vs. polythetic
Full lecture: http://bit.ly/K-means The aim of clustering is to partition a population into sub-groups (clusters). Clusters can be monothetic (where all cluster members share some common property) or polythetic (where all cluster members are similar to each other in some sense).
From playlist K-means Clustering
Clustering (2): Hierarchical Agglomerative Clustering
Hierarchical agglomerative clustering, or linkage clustering. Procedure, complexity analysis, and cluster dissimilarity measures including single linkage, complete linkage, and others.
From playlist cs273a
Hierarchical Clustering 5: summary
[http://bit.ly/s-link] Summary of the lecture.
From playlist Hierarchical Clustering
We will look at the fundamental concept of clustering, different types of clustering methods and the weaknesses. Clustering is an unsupervised learning technique that consists of grouping data points and creating partitions based on similarity. The ultimate goal is to find groups of simila
From playlist Data Science in Minutes
What are Connected Graphs? | Graph Theory
What is a connected graph in graph theory? That is the subject of today's math lesson! A connected graph is a graph in which every pair of vertices is connected, which means there exists a path in the graph with those vertices as endpoints. We can think of it this way: if, by traveling acr
From playlist Graph Theory
Clustering 2: Monothetic vs polythetic
From playlist Clustering Algorithms
Reinhold Schneider - Tensor Networks (QC-DMRG) in a Complete Active Space Coupled Cluster Method
Recorded 29 March 2022. Reinhold Schneider of Technische Universität Berlin, Institut für Mathematik, FG Modellierung, Simulation & Optimieru presents "Tensor Networks (QC-DMRG) in a Complete Active Space Coupled Cluster Method" at IPAM's Multiscale Approaches in Quantum Mechanics Workshop
From playlist 2022 Multiscale Approaches in Quantum Mechanics Workshop
Reinhold Schneider - Multi-Reference Coupled Cluster for Computation of Excited States & Tensors
Recorded 29 March 2023. Reinhold Schneider of the Technische Universität Berlin presents "A Multi-Reference Coupled Cluster Method for the Computation of Excited States and Tensor Networks (QC-DMRG)" at IPAM's Increasing the Length, Time, and Accuracy of Materials Modeling Using Exascale C
From playlist 2023 Increasing the Length, Time, and Accuracy of Materials Modeling Using Exascale Computing
Mod-01 Lec-23 Electrical, Magnetic and Optical Properties of Nanomaterials
Nanostructures and Nanomaterials: Characterization and Properties by Characterization and Properties by Dr. Kantesh Balani & Dr. Anandh Subramaniam,Department of Nanotechnology,IIT Kanpur.For more details on NPTEL visit http://nptel.ac.in.
From playlist IIT Kanpur: Nanostructures and Nanomaterials | CosmoLearning.org
Serhiy Yanchuk - Adaptive dynamical networks: from multiclusters to recurrent synchronization
Recorded 02 September 2022. Serhiy Yanchuk of Humboldt-Universität presents "Adaptive dynamical networks: from multiclusters to recurrent synchronization" at IPAM's Reconstructing Network Dynamics from Data: Applications to Neuroscience and Beyond. Abstract: Adaptive dynamical networks is
From playlist 2022 Reconstructing Network Dynamics from Data: Applications to Neuroscience and Beyond
Lecture 08 -Jack Simons Electronic Structure Theory- Coupled-cluster theory
Coupled-cluster (CC) theory; analogy to cluster expansion in statistical mechanics; the CC equations are quartic. (1)Jack Simons Electronic Structure Theory- Session 1- Born-Oppenheimer approximation http://www.youtube.com/watch?v=Z5cq7JpsG8I (2)Jack Simons Electronic Structure Theory
From playlist U of Utah: Jack Simons' Electronic Structure Theory course
Muhammad Hassan - Development of a posteriori error estimates for the coupled cluster equations
Recorded 03 May 2022. Muhammad Hassan of Sorbonne Université, Laboratoire Jacques-Louis Lions, presents "Towards the development of a posteriori error estimates for the coupled cluster equations" at IPAM's Large-Scale Certified Numerical Methods in Quantum Mechanics Workshop. Abstract: Cou
From playlist 2022 Large-Scale Certified Numerical Methods in Quantum Mechanics
Percolation: a Mathematical Phase Transition
—————SOURCES———————————————————————— Percolation – Béla Bollobás and Oliver Riordan Cambridge University Press, New York, 2006. Sixty Years of Percolation – Hugo Duminil-Copin https://www.ihes.fr/~duminil/publi/2018ICM.pdf Percolation – Geoffrey Grimmett volume 321 of Grundlehren der Ma
From playlist Prob and Stats
Galaxy Cluster Cosmology with the South Pole Telescope by Sebastian Bocquet
Program Cosmology - The Next Decade ORGANIZERS : Rishi Khatri, Subha Majumdar and Aseem Paranjape DATE : 03 January 2019 to 25 January 2019 VENUE : Ramanujan Lecture Hall, ICTS Bangalore The great observational progress in cosmology has revealed some very intriguing puzzles, the most i
From playlist Cosmology - The Next Decade
From playlist daytum Free Webinar Series
Clustering Introduction - Practical Machine Learning Tutorial with Python p.34
In this tutorial, we shift gears and introduce the concept of clustering. Clustering is form of unsupervised machine learning, where the machine automatically determines the grouping for data. There are two major forms of clustering: Flat and Hierarchical. Flat clustering allows the scient
From playlist Machine Learning with Python
Daniel Fisher - Random quantum Ising spin chains
Random transfer field Ising spin chains are a prototypical example of the interplay between quenched randomness and quantum fluctuations. An approximate real-space renormalization group analysis that becomes exact near the phase zero-temperature phase transition will be presented. Scalin
From playlist 100…(102!) Years of the Ising Model