Bayesian Inference Courses and Certifications

Probabilistic AI School

Variational Inference and Optimization - Lecture 2

Explore advanced variational inference and optimization techniques for probabilistic AI, focusing on practical applications and cutting-edge methodologies.

• YouTube
• 1 hour 49 minutes
• On-Demand
• Free Video

Probabilistic AI School

Variational Inference and Optimization - Lecture 1

Explore variational inference and optimization techniques in probabilistic AI, covering key concepts and applications for advanced machine learning.

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

Probabilistic AI School

Bayesian Workflow

Learn Bayesian workflow techniques for probabilistic modeling, from problem formulation to model evaluation and iteration, enhancing your data analysis skills.

• YouTube
• 2 hours 4 minutes
• On-Demand
• Free Video

Probabilistic AI School

Variational Inference and Optimization - Lecture 3

Explore advanced concepts in variational inference and optimization with expert insights from Langseth, Masegosa, and Nielsen at the Nordic Probabilistic AI School.

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

Probabilistic AI School

Bayesian Neural Networks

Explore Bayesian Neural Networks: foundations, applications, and advanced techniques for probabilistic deep learning models.

• YouTube
• 2 hours 7 minutes
• On-Demand
• Free Video

Probabilistic AI School

Bayesian Workflow

Learn Bayesian workflow techniques for probabilistic modeling, including prior specification, model checking, and posterior predictive checks.

• YouTube
• 2 hours 19 minutes
• On-Demand
• Free Video

Probabilistic AI School

Variational Inference and Optimization - Lecture 1

Explore variational inference and optimization techniques in probabilistic AI, covering key concepts and applications in machine learning and data analysis.

• YouTube
• 1 hour 44 minutes
• On-Demand
• Free Video

Center for Language & Speech Processing(CLSP), JHU

A Bayesian View of Inductive Learning in Humans and Machines - 2004

Explore how humans make successful generalizations from limited evidence through Bayesian inferences constrained by implicit domain theories, with applications to machine learning.

• YouTube
• 1 hour 26 minutes
• On-Demand
• Free Video

Fields Institute

Active Inference and Belief Propagation in the Brain

Explore how the brain uses deep temporal models and Bayesian belief updating to process information, simulate behavior, and generate electrophysiological responses through active inference.

• YouTube
• 1 hour 40 minutes
• On-Demand
• Free Video

Fields Institute

Active Inference and Artificial Curiosity

Discover how active Bayesian inference enables agents to learn from minimal data, develop artificial curiosity, and experience insight through epistemic behavior and model selection.

• YouTube
• 1 hour 48 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

HJ-Sampler - A Bayesian Sampler for Inverse Problems of Stochastic Processes by Leveraging Hamilton-Jacobi PDEs

Discover a novel Bayesian sampling algorithm for stochastic process inverse problems using Hamilton-Jacobi PDEs and score-based generative models with practical numerical examples.

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

Topos Institute

Update Rules of Pearl and Jeffrey in Probabilistic Updating

Explore the differences between Pearl and Jeffrey's probabilistic updating rules, their applications in multiple data scenarios, and their role in machine learning algorithms like Expectation Maximization.

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

Simons Institute

Amortised Inference Meets LLMs: Algorithms and Implications for Faithful Knowledge Extraction

Explore Bayesian inference techniques for LLMs, including Monte Carlo methods and variational inference, to solve challenges in constrained generation, reasoning, and knowledge extraction while maintaining uncertainty awareness.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video

Conference GSI

Variational Gaussian Approximation of the Kushner Optimal Filter

Explore the Variational Gaussian approximation technique for optimizing the Kushner filter, enhancing signal processing and estimation capabilities.

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

Society for Industrial and Applied Mathematics

Computational Methods in Ice-sheet Modeling - Uncertainty Quantification and Optimization

Explore advanced computational methods for ice-sheet modeling, including parameter inversion, uncertainty quantification, and multi-fidelity techniques for efficient glacier mass change estimation.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Video