Courses from 1000+ universities
India banned Telegram after the NEET paper leak led to a retest for 2.28 million students. Class Central studied the scam, the money trail, and other platforms the leaks could move to.
600 Free Google Certifications
Artificial Intelligence
Language Learning
Data Analysis
Mathematical and Computational Methods
AP® Microeconomics
Competitive Strategy
Organize and share your learning with Class Central Lists.
View our Lists Showcase
Explore quantum persistent homology algorithms for pattern recognition in data, leveraging quantum computing's potential to enhance traditional Topological Data Analysis methods and improve efficiency.
Exploring persistent function-based machine learning for drug design, focusing on novel molecular representations and their application in improving predictive models for drug discovery.
Explore topological approaches to robotic motion planning by computing homology groups of constrained robotic arm motion spaces using Morse theory and combinatorial methods.
Discover how to navigate and contribute to DONUT, a specialized database cataloging practical applications of topology across various fields and research domains.
Explore Rips-type ellipsoid complexes using local PCA to better capture manifold geometry, with theoretical stability guarantees for persistence barcodes under data variations.
Explore adversarial robustness in persistent homology, connecting topological data analysis to minimum cut problems in simplicial complexes for outlier-resistant feature detection.
Explore CL-complexes, a novel cell-complex framework for representing finite poset homotopy types, extending beyond traditional order complexes with applications to higher-order nerve theorems.
Discover a threshold-free method using persistent homology to classify the stratospheric polar vortex into displaced, split, or normal states.
Explore innovative time series forecasting using Graph Neural Networks and multipersistence, applied to traffic flow, cryptocurrency prices, and COVID-19 hospitalizations.
Exploring parallel decomposition of persistence modules using interval bases, with applications in Topological Data Analysis and connections to the Hodge Laplacian.
Explore simplicial neural networks, a generalization of graph neural networks for multi-dimensional data, and their applications in imputing missing data on coauthorship complexes.
Exploring how mathematics and AI revolutionize biosciences, focusing on tackling challenges in biological data complexity, dimensionality, and nonlinearity to enhance AI's capabilities in drug design and viral mutation prediction.
Exploring efficient computation of homological representations in dynamical systems, with applications to differential equations and parameter space analysis.
Principal components analysis for quiver representations: dimensionality reduction, comparison, and optimization techniques for vector-space valued representations across pure and applied mathematics.
Explore topological signals, higher-order Laplacians, and the Dirac operator in network science. Learn about spectral properties, diffusion dynamics, and topological synchronization in simplicial complexes and multiplex networks.
Get personalized course recommendations, track subjects and courses with reminders, and more.