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 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

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

Contrastive Explanation Learning for Reinforcement Learning

Discover how contrastive explanation methods enhance reinforcement learning interpretability through Syracuse University's research presented at METACOG-25.

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

Hyperdimensional Computing Hardware - Racetrack Memories

Explore novel hardware techniques using racetrack memories for efficient hyperdimensional computing in this 12-minute research presentation from METACOG-25.

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

Neural Networks with Symbolic Equivalents

Explore dILP and LNN systems where neural networks are constructed from symbolic primitives in neurosymbolic AI through the Kautz taxonomy framework.

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

Metacognition in Content-Centric Cognitive Modeling

Explore Prof. Sergei Nirenburg's insights on metacognition within content-centric cognitive modeling frameworks and their applications in AI research.

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

Combinatorial Testing for Metacognitive AI

Discover how combinatorial testing techniques can enhance metacognitive AI systems through practical applications and research insights from VT NSI.

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

Neural Manipulation of Symbols - Kautz 2 and Kautz 3 Frameworks for Symbolic Regression and Program Generation

Explore neural networks that manipulate symbols for symbolic regression and program generation using Kautz 2 and Kautz 3 frameworks in this 46-minute deep dive.

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

Cross-Fold Validation

Master cross-fold validation techniques to improve model evaluation and prevent overfitting in machine learning projects.

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

Neuro-Symbolic AI - Reviews and Tutorials

Explore comprehensive AI fundamentals from logic programming to deep learning, covering neuro-symbolic reasoning, machine learning bias, and practical PyReason tutorials.

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

LLM Tutorial - Introduction to Language Models, Prompt Engineering, and Encoder-Decoder Architectures

Discover LLM fundamentals, prompt engineering techniques, and explore both encoder and decoder architectures while understanding model limitations and hallucinations.

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

ML Foundations IV - Advanced Deep Learning

Master advanced deep learning concepts including transformers, BERT, GPT models, prompt engineering, reinforcement learning, and neural network optimization techniques.

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

ML Foundations V - Unsupervised and Non-Parametric Methods

Explore unsupervised learning, clustering algorithms, k-nearest neighbors, and association rule mining techniques in this comprehensive machine learning foundations session.

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