Exactly Solvable 2D Conformal Field Theory - Lecture 4: Degenerate 4-Point Functions
Explore degenerate 4-point functions and analytic formulas for 2-point and 3-point structure constants in exactly solvable 2D conformal field theories. Gain insights into bootstrap approach and local conformal symmetry.
Predicting Healthcare Insurance Costs with Python - Real-World Data Science Problem Solving
Predict healthcare insurance costs using Python and machine learning. Clean data, visualize with pandas, and apply scikit-learn for linear regression in this hands-on tutorial with real-world data analysis.
Introduction to Model Fitting - Gravitational Lensing and Graphical Modeling
Explore gravitational lensing model fitting techniques, from traditional methods to innovative graphical modeling, and learn about PyAutoFit for streamlined probabilistic programming.
Statistical Analysis in Cosmology - Part 1
Explore Bayesian statistics, likelihood sampling, chi-square, and covariance matrix in cosmology. Learn parameter estimations in 2-point statistics and Markov Chain Monte Carlo.
The Entropic Dynamics Approach to Quantum Mechanics
Explore the Entropic Dynamics framework for reconstructing Quantum Mechanics, focusing on ontic and epistemic variables, probability distributions, and the derivation of key quantum principles.
Weak Limits for Entropic Optimal Transport - Part II
Explore weak limits for entropic optimal transport, covering parametric cases, duality, proofs, and connections to improved CLT and convex optimization.
Data-Driven Latent Representations for Time-Dependent Problems - Lecture 3
Explore data-driven latent representations for time-dependent problems, focusing on applications in climate downscaling, superresolution, and optimal transport.
Randomness and Complexity - Lecture 1
Explore the intersection of randomness and complexity in mathematics, delving into key concepts and their applications in discrete mathematics and computer science.
Wasserstein Gradient Flows and Applications to Sampling in Machine Learning - Lecture 1
Explore Wasserstein gradient flows and their applications to sampling in machine learning through an in-depth lecture by Anna Korba.
Wasserstein Gradient Flows and Applications to Sampling in Machine Learning - Lecture 3
Explore Wasserstein gradient flows and their applications to sampling in machine learning with Anna Korba's advanced lecture on this complex mathematical topic.
2D Percolation Revisited
Explore 2D percolation theory with Fields Medalist Stanislav Smirnov in this IMPA 70th anniversary conference talk. Gain insights into advanced mathematical concepts and recent developments in the field.
Statistical Network Analysis - Course 2
Explore statistical network analysis techniques with experts from Texas A&M and Wisconsin. Gain insights into discrete probability, collaborate on open problems, and advance your research in this month-long program.
Statistical Network Analysis - Course 2
Explore statistical network analysis techniques with experts from Texas A&M and Wisconsin. Gain insights into discrete probability, collaborate on open problems, and advance your research in this month-long program.
Statistical Network Analysis - Course 2
Explore statistical network analysis techniques with experts from Texas A&M and Wisconsin. Gain insights into discrete probability, collaborate on open problems, and advance your research in this month-long program.
Empower an End-to-End Scalable and Interpretable Data Science Ecosystem Using Statistics, AI and Domain Science
Explore scalable, interpretable data science using statistics, AI, and domain expertise. Gain insights from Harvard professor Xihong Lin on analyzing complex genomic and health data.
Data in our Day to Day: Beyond the Basics
Explore advanced data concepts and applications in otolaryngology, enhancing clinical decision-making and research practices beyond fundamental principles.
Wigner's Semicircle Distribution as Limit Distribution
Explore the Wigner distribution as a limit of eigenvalue distributions in random matrices, with a focus on probability theory and mathematical analysis.
Correlations, Representations and the Emergence of Spacetime
Explore the emergence of spacetime and dimensional changes at high energies through an information-theoretic approach, examining bosonic and fermionic interactions.
Stochastic Partial Differential Equations and Regularity Structures - Award Lecture
Explore groundbreaking work on stochastic partial differential equations, revolutionizing mathematical modeling of random physical systems with the theory of regularity structures.
Ocean Diffusivity: Stochastic Approaches in Numerical Modeling
Explore stochastic approaches in ocean modeling, including Monte-Carlo methods, perturbed conditions, and stochastic dissipation operators for improved numerical simulations.
Nonequilibrium Response Theory for Soft and Active Matter
Explore nonequilibrium statistical physics for colloidal suspensions and active particles using the ITT framework. Examine stochastic processes, nonlinear response, and applications in shear and microswimmers.