Mutual Information Courses and Certifications

Introduction to Information Theory

12 reviews

This tutorial introduces fundamental concepts in information theory.

• Complexity Explorer
• 1 hour
• On-Demand
• Free Online Course

Information Theory of Deep Learning - Naftali Tishby

Explores the connection between deep learning and information theory, offering new insights into neural network design, generalization, and optimization through an information bottleneck framework.

• YouTube
• 1 hour 25 minutes
• On-Demand
• Free Video

Dimensionality Reduction with Feature Selection

Master advanced feature selection techniques to optimize machine learning models through variance analysis, univariate selection, mutual information, and recursive elimination methods.

• CodeSignal
• On-Demand
• Free Certificate

IEEE Signal Processing Society

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

Blessings of Dimensionality for Gaussian Latent Factor Models

Explore how high-dimensional data analysis can benefit from restricted latent factor overlaps, with applications in brain fMRI and financial markets.

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

Rational Ignorance - Optimal Learning from Complex Mechanistic Models

Explore optimal Bayesian learning from complex models, challenging traditional approaches and proposing a new method to maximize expected information while avoiding bias in multiparameter systems.

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

The Information Knot - Tying Sensing and Action; Emergence Theory of Representation Learning

Explore information theory, representation learning, and AI concepts with NYU's Stefano Soatto. Delve into information bottlenecks, mutual information, and disentangling in this advanced seminar on modern AI.

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

Region Mutual Information Loss for Semantic Segmentation

Explore advanced techniques in semantic segmentation, including region mutual information loss, à trous convolutions, and multi-scale features for improved image analysis and understanding.

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

IIT Kanpur;  NPTEL

An Introduction to Information Theory

Explore fundamental concepts of information theory, including entropy, source compression, channel capacity, and coding techniques for efficient data transmission and storage.

• Swayam
• 8 weeks
• On-Demand
• Free Online Course

Professor Knudson

Applied Probability and Statistics Seminar Series

Explore cutting-edge statistical applications in health, astrophysics, and healthcare equity through expert-led seminars on football injuries, dark matter detection, and racial disparities in prostate cancer outcomes.

• YouTube
• 2 hours 30 minutes
• On-Demand
• Free Video

Alan Turing Institute

Sequential Design Based on Mutual Information for Computer Experiments - Joakim Beck, KAUST

Explore uncertainty quantification using Gaussian Process emulators for complex systems. Learn about sequential design methods, mutual information criteria, and applications in climate, tsunami, and earthquake modeling.

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

Edan Meyer

Learning Fast with No Goals - VISR Explained

Explore rapid generalization in Reinforcement Learning with VISR, focusing on successor features and goal-conditioned policies for efficient task adaptation without rewards.

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

Institute for Pure & Applied Mathematics (IPAM)

Quantum Error Correcting for Gravity in the Large-N Limit - IPAM at UCLA

Explore quantum error correcting codes for large-N limit theories, focusing on gravitational duals and emerging features. Covers asymptotic operator algebra results and information theoretic constraints.

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

Centrum Fizyki Teoretycznej PAN

Distinguishing Between Redundancy and Consensus in Quantifying Quantum Objectivity

Explore rigorous definitions of "redundancy" and "consensus" in quantum objectivity, examining their distinct roles in the quantum-to-classical transition and implications for quantum Darwinism.

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

Uncertainty in Artificial Intelligence

Quantifying Aleatoric and Epistemic Uncertainty in Machine Learning - Session 2

Explore critical analysis of uncertainty quantification in machine learning, examining conditional entropy and mutual information as measures for aleatoric and epistemic uncertainty.

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