Neuro Symbolic Courses

Introduction to Propositional Logic

1 rating

Explore propositional logic fundamentals: atoms, operators, truth tables, natural language meaning, and inference rules for enhanced logical reasoning skills.

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

Markov Random Fields, Markov Chains, and Markov Logic Networks - Probabilistic Graphical Models Tutorial

1 rating

Explore Markov Random Fields, Logic Networks, and Chains. Dive into probabilistic graphical models with Professor Simari, covering key concepts and applications in AI and machine learning.

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

PyReason and Abduction for Trajectory Generation

Explore combining PyReason's annotated logic with abductive inference for robust human movement trajectory generation, countering anomaly detection.

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

Constraint Satisfaction Problems: Consistency Algorithms - Part 6

Explore consistency algorithms for constraint satisfaction problems in AI, covering formulation, solving methods, and domain splitting.

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

Uncertainty Quantification in Metacognition

Explore uncertainty quantification in metacognition and its applications in AI research, focusing on DARPA-funded efforts and advancements in neuro-symbolic approaches.

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

Introduction to PyReason: Pet Store Tutorial

Learn PyReason fundamentals through a practical pet store example, covering rules, facts, annotations, and execution in a hands-on demonstration of this neuro-symbolic AI tool.

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

Trajectory Generation via Abductive Inference

Discover how abductive inference enables efficient geospatial trajectory generation through innovative logical programming and deep learning approaches for AI advancement.

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

Interpretable and Data-Efficient Learning for Autonomous Systems

Explore cutting-edge approaches to autonomous systems through interpretable learning methods and data-efficient techniques, focusing on the intersection of symbolic AI and deep learning.

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

Prompt Engineering for Neuro-Symbolic AI - Part 2

Dive into advanced prompt engineering techniques, exploring the intersection of symbolic methods and deep learning for more effective AI interactions and development.

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

MDS-A: New Dataset for Test-Time Adaptation in Object Detection

Discover the "Multiple Distribution Shift - Aerial" (MDS-A) dataset for evaluating test-time adaptation models, featuring multiple training and test sets for researching object detection across various distributions.

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

PyReason ML Integration Tutorial - Time Series Reasoning

Dive into time series reasoning with PyReason's ML integration, building on Part 1 concepts through a practical temporal example with complete code resources.

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

Probabilistic Foundations of Metacognition via Hybrid AI

Explore the probabilistic foundations of metacognition in AI through error correction and detection rules, explaining experimental results and theoretical advances in neuro-symbolic approaches.

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

PyReason ML Integration Tutorial - Binary Classifier

Learn how to integrate machine learning classifier models with PyReason in this tutorial, with access to full code examples and comprehensive resources for implementation.

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

Visual Concept Grounding for Lifelong Learning

Explore visual concept grounding for lifelong learning with Yezhou Yang, delving into active perception and cutting-edge AI research at Arizona State University.

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

Certifying Trustworthy Deep Learning Systems

Explore techniques for certifying trustworthiness in deep learning systems with expert insights from Linyi Li, enhancing AI reliability and safety.

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