IEEE Signal Processing Society Courses

Geometric Deep Learning for Drug Discovery

1 review

Explore geometric deep learning techniques for drug discovery, covering graph neural networks, molecule generation, and retrosynthetic prediction. Gain insights into cutting-edge research and applications in pharmaceutical development.

• YouTube
• 58 minutes
• On-Demand
• Free Video

A Tour in the Real-World Challenges Faced by Law Enforcement Agencies When Dealing With Images

1 review

Explore real-world challenges in law enforcement image analysis, covering infrared footage, lens distortion, perspective issues, compression artifacts, and AI impacts on forensic video interpretation.

• YouTube
• 59 minutes
• On-Demand
• Free Video

Graph Neural Networks for Multi-Agent Learning

Learn to apply Graph Neural Networks in multi-agent systems, exploring their potential for collaborative decision-making and distributed intelligence in complex environments.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Scientific Integrity Verification Through Image Forensics

Explore image forensics techniques for verifying scientific integrity, uncovering manipulations, and ensuring research authenticity in academic publications.

• YouTube
• 46 minutes
• On-Demand
• Free Video

Graph Signal Processing for Neuroimaging - When Anatomy Meets Activity

Explore brain imaging through graph signal processing, connecting anatomy and activity. Learn MRI techniques, brain graphs, and innovative analysis methods for neuroimaging data.

• YouTube
• 1 hour 6 minutes
• On-Demand
• Free Video

Robustness of Graph Neural Networks

Explore techniques to enhance robustness of Graph Neural Networks, including adaptive attacks, certificates, and collective reasoning. Learn strategies to improve model resilience in graph-based machine learning.

• YouTube
• 56 minutes
• On-Demand
• Free Video

Subgraph-Based Networks for Expressive, Efficient, and Domain-Independent Graph Learning

Explore advanced graph learning techniques using subgraph-based networks for expressive, efficient, and domain-independent applications in data science and signal processing.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Single View and Multiview Signed Graph Learning - Applications to Gene Regulatory Network Inference

Explore graph learning techniques for gene regulatory network inference, focusing on single-view and multi-view approaches, their applications, and computational challenges in bioinformatics.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Graph Constructions for Machine Learning Applications - New Insights and Algorithms

Explore graph constructions for machine learning, covering signal variation, sampling, and semisupervised learning. Gain insights into theoretical analysis and applications in deep learning geometry.

• YouTube
• 1 hour 14 minutes
• On-Demand
• Free Video

Graph Neural Networks Are Dynamic Programmers

Explore how Graph Neural Networks function as dynamic programmers, bridging classical algorithms with neural approaches for optimal path finding and algorithmic reasoning.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Increasing Value to SPS Members Through IEEE HAC-SIGHT

Learn how IEEE HAC/SIGHT offers high-impact humanitarian engagement opportunities, advancing technologies for marginalized communities worldwide. Discover achievements, benefits, collaborations, and ways to get involved in this impactful initiative.

• YouTube
• 58 minutes
• On-Demand
• Free Video

Learning by Transference in Large Graphs

Explore graph theory, convergence, and transferability in large networks. Learn about graph neural networks, filters, and applications in multi-robot systems and signal processing.

• YouTube
• 1 hour 9 minutes
• On-Demand
• Free Video

Causal Inference on Networks to Characterize Disinformation Narrative Propagation

Explore techniques for detecting and analyzing disinformation spread on social networks using causal inference, focusing on network construction, influence scoring, and bot detection.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Modeling Physical Structure and Dynamics Using Graph-Based Machine Learning

Explore graph-based machine learning for modeling physical structures and dynamics, covering algorithms, architectures, simulations, and applications in various domains.

• YouTube
• 1 hour 15 minutes
• On-Demand
• Free Video

Model-Based Deep Learning: Deep Equilibrium Models and Proximal Gradient Maps

Explore model-based deep learning, deep equilibrium models, and their applications in image recovery, focusing on robustness, safety, and efficiency in undersampled data scenarios.

• YouTube
• 1 hour 10 minutes
• On-Demand
• Free Video