Conformal prediction (CP) is a set of algorithms devised to assess the uncertainty of predictions produced by a machine learning model. CP algorithms do this by computing and comparing nonconformity measures (often referred to as α-values), of examples from the training set, and compare these with measure computed for examples from a test set. Conformal predictors can be divided into inductive and transductive. These mainly differ in their computational complexity and whether they can be applied to regression or classification tasks. Inductive algorithms train one or several machine learning models which are re-used for future test objects, and can be used for both classification and regression tasks, whereas transductive algorithms re-train the model for every test object, and can only be used for classification tasks. Conformal prediction requires a user-specified significance level for which the algorithm should produce its predictions. This significance level restricts the frequency of errors that the algorithm is allowed to make. For example, a significance level of 0.1 means that the algorithm can make at most 10% erroneous predictions. To meet this requirement, the output is a set prediction, instead of a point prediction produced by standard supervised machine learning models. For classification tasks, this means that predictions are not a single class, for example 'cat', but instead a set like {'cat', 'dog'}. Depending on how good is the underlying model (how well it can discern between cats, dogs and other animals) and the specified significance level, these sets can be smaller or larger. For regression tasks, the output is prediction intervals, where a smaller significance level (less allowed errors) produces wider intervals which are less specific, and vice versa – more allowed errors produces tighter prediction intervals. (Wikipedia).
Conformal Field Theory (CFT) | Infinitesimal Conformal Transformations
Conformal field theories are used in many areas of physics, from condensed matter physics, to statistical physics to string theory. They are defined as quantum field theories that are invariant under so-called conformal transformations. In this video, we will investigate these conformal tr
From playlist Particle Physics
Symposium on Geometry Processing 2017 Graduate School Lecture by Keenan Crane https://www.cs.cmu.edu/~kmcrane/ http://geometry.cs.ucl.ac.uk/SGP2017/?p=gradschool#abs_conformal_geometry Digital geometry processing is the natural extension of traditional signal processing to three-dimensi
From playlist Tutorials and Lectures
SGP2018 Graduate School | July 7-11 | Paris, France Speaker: Keenan Crane, Carnegie Mellon University Abstract: Digital geometry processing is the natural extension of traditional signal processing to three-dimensional geometric data. In recent years, methods based on so-called conformal
From playlist Tutorials and Lectures
Conformal Field Theory (CFT) | More on Infinitesimal Conformal Transformations
Conformal field theories are quantum field theories that are invariant under so-called conformal transformations. In this video, we will investigate these conformal transformations in three or more dimensions. More information and details can be found in the excellent book "Introduction
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How to Make Predictions in Regression Analysis
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys How to Make Predictions in Regression Analysis
From playlist Statistics
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From playlist The First CHALKboard
Rod Gover - An introduction to conformal geometry and tractor calculus (Part 4)
After recalling some features (and the value of) the invariant « Ricci calculus » of pseudo‐Riemannian geometry, we look at conformal rescaling from an elementary perspective. The idea of conformal covariance is visited and some covariant/invariant equations from physics are recovered in
From playlist Ecole d'été 2014 - Analyse asymptotique en relativité générale
From playlist Plenary talks One World Symposium 2020
Assumption-free prediction intervals for black-box regression algorithms - Aaditya Ramdas
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From playlist Mathematics
Rod Gover - An introduction to conformal geometry and tractor calculus (Part 1)
After recalling some features (and the value of) the invariant « Ricci calculus » of pseudo‐Riemannian geometry, we look at conformal rescaling from an elementary perspective. The idea of conformal covariance is visited and some covariant/invariant equations from physics are recovered in
From playlist Ecole d'été 2014 - Analyse asymptotique en relativité générale
8 Fundamental Flavors and the sill of the Conformal Window by Anna Hasenfratz
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From playlist NUMSTRING 2022
Recent progress in predictive inference - Emmanuel Candes, Stanford University
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Verifying the predictions of Conformal Bootstrap through lattice calculations by Prasad Hegde
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From playlist Bangalore Area Strings Meeting - 2017
Rod Gover - An introduction to conformal geometry and tractor calculus (Part 3)
After recalling some features (and the value of) the invariant « Ricci calculus » of pseudo‐Riemannian geometry, we look at conformal rescaling from an elementary perspective. The idea of conformal covariance is visited and some covariant/invariant equations from physics are recovered in
From playlist Ecole d'été 2014 - Analyse asymptotique en relativité générale
Alessandro Vichi - Anatomy of the Ising model from Conformal Bootstrap
The Ising model is the one the simplest and yet non-trivial Conformal Field Theory. For decades it has been a dream to study such an intricate strongly coupled theory non-perturbatively using symmetries and other consistency conditions. This idea, called the conformal bootstrap, saw some s
From playlist 100…(102!) Years of the Ising Model
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PROGRAM NONPERTURBATIVE AND NUMERICAL APPROACHES TO QUANTUM GRAVITY, STRING THEORY AND HOLOGRAPHY (HYBRID) ORGANIZERS: David Berenstein (University of California, Santa Barbara, USA), Simon Catterall (Syracuse University, USA), Masanori Hanada (University of Surrey, UK), Anosh Joseph (II
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Rod Gover - An introduction to conformal geometry and tractor calculus (Part 2)
After recalling some features (and the value of) the invariant « Ricci calculus » of pseudo‐Riemannian geometry, we look at conformal rescaling from an elementary perspective. The idea of conformal covariance is visited and some covariant/invariant equations from physics are recovered in
From playlist Ecole d'été 2014 - Analyse asymptotique en relativité générale