Lectures related to Inductive probability

Inductive Propositions: Reasoning and Evaluation Techniques

Discusses inductive propositions, their definitions, and applications in reasoning and evaluation techniques in Coq.

Covers the fundamentals of Bayesian estimation, focusing on the application of Bayes' Theorem in scalar estimation.

Explores optimal Bayesian inference, denoising, scalar estimation, and phase transitions.

Inductive Propositions: Understanding Evaluation in Coq

Covers inductive propositions in Coq, focusing on evaluation rules for arithmetic expressions and their applications in defining partial and non-deterministic functions.

Inductive Series

Covers the concept of inductive series and their convergence conditions.

Generative Models: Logistic Regression & Gaussian Distribution

Explores generative models, logistic regression, and Gaussian distribution for approximating posterior probabilities and optimizing model performance.

Estimation & Bayesian Inference

Covers demousing, estimation, Bayesian inference, likelihood, AWGN, and more.

Verifying Programs with Stainless: How Stainless Works

Explores the inner workings of the Stainless framework, emphasizing verification-aware transformations and dependent type checking.

Coq Workshop: Introduction to Interactive Theorem Proving

Introduces Coq, an interactive theorem assistant based on the Curry-Howard isomorphism.

Uncertain Reasoning: Bayesian Networks

Explores uncertain reasoning, Bayesian networks, and stochastic resolution, emphasizing the importance of probabilistic logic and abduction.

Gaussian Naive Bayes & K-NN

Covers Gaussian Naive Bayes, K-nearest neighbors, and hyperparameter tuning in machine learning.

Bayesian Inference: Estimation & Demystification

Covers the concepts of Demystification, Estimation, and Bayesian Inference in the context of Bayesian statistics.

Inference Problems & Spin Glass Game

Covers inference problems related to the Spin Glass Game and the challenges of making mistakes with preb P.

Risk Analysis Methods: Part 1

Explores risk analysis methods, including failure modes analysis and criticality assessment, emphasizing the importance of preliminary risk analysis.

Statistical Vision Problems

Explores statistical vision problems, evaluating algorithms for hidden signal estimation and the challenges of phase transitions.

Polymorphism in Coq: Data Structures and Functions

Covers polymorphism in Coq, focusing on data structures and functions like lists, length, and append.

Coq Workshop: Inductive Data Types and Proofs

Covers the definition of an inductive data type in Coq and how to build proofs interactively using tactics.

Mathematical Induction: Principle and Example

Introduces the principle of mathematical induction through an example.

Risk Analysis and Management

Explores risk analysis and management methods for civil engineering projects, emphasizing the importance of identifying adverse events and security barriers.

Bayes Theorem: Applications and Interpretation

Explores the practical utility of Bayes Theorem in inverting perspectives and efficiently calculating conditional probabilities.