Physarum can compute shortest paths

Related lectures (35)

Explores belief propagation in random graphs and Bethe free entropy.

Explores concurrent programming theory and practice, covering system models, cache coherence, and graph processing.

Explores memory management, graph representation, and traversal algorithms in Python, emphasizing BFS and DFS.

Introduces the basics of graphs and networks, covering definitions, paths, trees, flows, circulation, and spanning trees.

Covers the Leighton-Rao algorithm for finding the sparsest cut in a graph, focusing on its steps and theoretical foundations.

Explores the Bellman Ford algorithm for finding the shortest path in graphs with negative edge weights.

Explores network flows, simplex method, linear programming, tree solutions, and dual solutions in optimization problems.

Covers solving bounded network flow problems by adjusting flow capacities and constraints, including binary programs.

Explores interlacing families, Ramanujan graphs, and their construction using signed adjacency matrices.

Covers translations, homotheties, and geometric transformations using vectors and matrices.

Explores isogenic graphs, spectral properties, and mathematical applications in modular forms and cryptography.

Explores Cheeger's inequality and its implications in graph theory.

Explores the construction of Ramanujan graphs using polynomials and addresses challenges with the probabilistic method.

Explores data-parallel programming with vector processors and SIMD, and introduces MapReduce, Pregel, and TensorFlow.

Page 2 of 2