Graph Theory Courses

Devoxx

Java on ARM - Theory, Applications and Workloads

Explore Java on ARM processors: theory, applications, and workloads. Learn about ARM servers, Java ARM port features, and performance optimization for specific use cases.

• YouTube
• 42 minutes
• Self-Paced
• Conference Talk

Devoxx

Java on ARM - Theory, Applications, and Workloads

Explore Java's performance on ARM processors, focusing on server applications, workload optimization, and recent improvements in the Java ARM port for cloud deployments.

• YouTube
• 48 minutes
• Self-Paced
• Conference Talk

IEEE

D-ARM - Disassembling ARM Binaries by Lightweight Superset Instruction Interpretation and Graph Modeling

Explore innovative techniques for disassembling ARM binaries using superset instruction interpretation and graph modeling, enhancing reverse engineering capabilities.

• YouTube
• 16 minutes
• Self-Paced
• Conference Talk

Devoxx

Graph-based ML for Automated Health Care Services

Leveraging graph-based machine learning and healthcare data to predict patient diagnoses in critical care units, showcasing the potential of automated healthcare through advanced ML techniques.

• YouTube
• 32 minutes
• Self-Paced
• Conference Talk

Fields Institute

Automorphic Forms and Representation Theory - Introduction to the Langlands Program

Explore the Langlands Program, connecting automorphic forms and representation theory in advanced mathematics, with insights from James Arthur of the University of Toronto.

• YouTube
• 59 minutes
• Self-Paced
• Free Video

Fields Institute

Automorphic Forms and Representation Theory - Introduction to the Langlands Program - Lecture 18

Explore the Langlands Program through automorphic forms and representation theory, delving into advanced mathematical concepts and their interconnections.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video

Fields Institute

Automorphic Forms and Representation Theory - Introduction to the Langlands Program - Lecture 14

Explore the Langlands Program, connecting automorphic forms and representation theory in advanced mathematics, with insights from James Arthur of the University of Toronto.

• YouTube
• 53 minutes
• Self-Paced
• Free Video

Fields Institute

Automorphic Forms and Representation Theory - Introduction to the Langlands Program - Lecture 3

Explore the Langlands Program through automorphic forms and representation theory, delving into advanced mathematical concepts and their interconnections.

• YouTube
• 43 minutes
• Self-Paced
• Free Video

Fields Institute

Automorphic Forms and Representation Theory - Introduction to the Langlands Program - Lecture 8

Explore the Langlands Program, connecting automorphic forms and representation theory in advanced mathematics, with insights from James Arthur.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

Fields Institute

Automorphic Forms and Representation Theory - Introduction to the Langlands Program - Lecture 7

Explore the Langlands Program through automorphic forms and representation theory, delving into advanced mathematical concepts and their interconnections.

• YouTube
• 54 minutes
• Self-Paced
• Free Video

Fields Institute

Automorphic Forms and Representation Theory - Introduction to the Langlands Program - Lecture 6

Explore the Langlands Program, connecting automorphic forms and representation theory in advanced mathematics, with insights from James Arthur of the University of Toronto.

• YouTube
• 56 minutes
• Self-Paced
• Free Video

Fields Institute

Automorphic Forms and Representation Theory - Introduction to the Langlands Program - Lecture 5

Explore the Langlands Program, connecting automorphic forms and representation theory in advanced mathematics, with insights from James Arthur of the University of Toronto.

• YouTube
• 53 minutes
• Self-Paced
• Free Video

Fields Institute

Approximation Theory of Deep Learning from the Dynamical Viewpoint

Explore deep learning approximation theory from a dynamical perspective, covering supervised learning, universal approximation, sequence modeling, and insights on various neural network architectures.

• YouTube
• 45 minutes
• Self-Paced
• Free Video

Fields Institute

Koopman Operator Theory Based Machine Learning of Dynamical Systems

Explore advanced machine learning techniques for dynamical systems using Koopman operator theory, presented by Igor Mezic from UC Santa Barbara.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video

Fields Institute

Why Interference Phenomena Do Not Capture the Essence of Quantum Theory

Explore why interference phenomena fail to fully encapsulate quantum theory's essence, challenging common misconceptions and deepening understanding of quantum mechanics.

• YouTube
• 43 minutes
• Self-Paced
• Free Video