Courses from 1000+ universities
$7.2 billion in combined revenue since 2020. $8 billion in lost market value. This merger marks the end of an era in online education.
600 Free Google Certifications
Management & Leadership
Cybersecurity
Digital Marketing
Learn Like a Pro: Science-Based Tools to Become Better at Anything
Uncommon Sense Teaching
Programming for Everybody (Getting Started with Python)
Organize and share your learning with Class Central Lists.
View our Lists Showcase
Explore approximation theory and closed ideals in analytic spaces, focusing on key theorems, inequalities, and applications in functional analysis.
Explore Sarason's Ha-plitz product problem, its implications in analytic function spaces, and recent developments in this challenging mathematical area.
Explore foliations on Shimura varieties, focusing on inseparable morphisms, characteristic P, and applications to surfaces and general cases in algebraic geometry.
Explore exceptional theta correspondences, focusing on Howe duality for G_2 x H pairs and a dichotomy theorem. Gain insights into local data correspondence, constraints, and reductive periods.
Explore uniqueness, harmonic representation, and representation theorems in Hardy spaces, advancing understanding of analytic function spaces and their applications.
Explore Hardy spaces with a focus on rotation, generalization, and approximate identities. Delve into uniform boundedness, Poisson PR constructions, and harmonic functions.
Explore Eisenstein cocycles, equivariant cohomology, and their applications to L-functions. Gain insights into recent constructions and their connections to theta kernels and arithmetic groups.
Explore supercuspidal parameters in representation theory, focusing on local Langlands conjecture, Fargues-Scholze theory, and applications to automorphic forms and wild ramification.
Explore global optimization techniques using the dual SONC cone and linear programming, with applications to minimizing exponential sums and multivariate real polynomials.
Explore connections between maximum likelihood estimation and invariant theory stability in log-linear and Gaussian group models, with applications to statistical modeling.
Explore numerical computation of monodromy action over real numbers, focusing on a new piece-wise approach for analyzing real solution sets, with applications in kinematics and mechanism calibration.
Explore optimal weighting for PCA in high-dimensional heteroscedastic data, improving recovery of underlying components and addressing challenges in modern applications with heterogeneous datasets.
Explore generalized compressed sensing with a family of measurement matrices, focusing on signal recovery from noisy linear measurements and the role of effective rank in guaranteeing accurate recovery.
Explore robust low-rank matrix completion using an alternating manifold proximal gradient method. Learn about its applications in computer vision, signal processing, and machine learning.
Explore rigidity theory's application to Gaussian graphical models, focusing on maximum likelihood thresholds and their implications for data analysis in genomics and other fields.
Get personalized course recommendations, track subjects and courses with reminders, and more.