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Related lectures (30)

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Learning from the Interconnected World with Graphs

Explores learning from interconnected data using graphs, covering challenges, GNN design, research landscapes, and democratization of Graph ML.

Graphs in Deep Learning: Applications and Techniques

Explores the role of graphs in deep learning, focusing on their structure, applications, and techniques for processing graph data.

Graph Neural Networks: Interconnected World

Explores learning from interconnected data with graphs, covering modern ML research goals, pioneering methods, interdisciplinary applications, and democratization of graph ML.

Graph Processing: Oracle Labs Insights

Explores the ubiquity of graphs in modern data and analytics, focusing on the shift in organizations' perception of graph technologies.

Graph Processing: Oracle Labs PGX

Covers graph processing with a focus on Oracle Labs PGX, discussing graph analytics, databases, algorithms, and distributed analytics challenges.

Graph Algorithms: Modeling and Traversal

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

Active Learning for Molecular Design

Covers machine learning approaches for material design, practical examples, and software tools for research.

Deep Learning: Graphs and Transformers Overview

Covers deep learning concepts, focusing on graphs, transformers, and their applications in multimodal data processing.

Fixed Points in Graph Theory

Focuses on fixed points in graph theory and their implications in algorithms and analysis.

Statistical Analysis of Network Data: Structures and Models

Explores statistical analysis of network data, covering graph structures, models, statistics, and sampling methods.