INI Seminar Room 2 Courses

From Scattered Samples to Fields of Distributions - Theory and Practice of Spatial Logistic Gaussian Processes

Explore Spatial Logistic Gaussian Processes theory and practice for transforming scattered data samples into comprehensive distribution fields.

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

Well-Posedness of Singular Switched Explicit Models and Potential Applications in Model-Based Reinforcement Learning for Constrained Systems

Explore well-posedness of singular switched explicit models and their applications in model-based reinforcement learning for constrained systems.

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

Stochastic Gradient with Least-Squares Control Variates

Explore advanced stochastic gradient methods using least-squares control variates to reduce variance in optimization algorithms for machine learning and uncertainty quantification.

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

From Scattered Samples to Fields of Distributions - Theory and Practice of Spatial Logistic Gaussian Processes

Discover how to transform scattered data samples into continuous probability distribution fields using Spatial Logistic Gaussian Processes theory and practical applications.

• YouTube
• 1 hour 8 minutes
• On-Demand
• Free Video

Nonparametric Smoothing of Directional and Axial Data

Explore nonparametric smoothing techniques for directional and axial data with Professor Lutz Duembgen from Universität Bern in this specialized statistical seminar.

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

Learning Controlled Stochastic Differential Equations

Discover advanced techniques for learning controlled stochastic differential equations in machine learning and statistical prediction uncertainty applications.

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

From Learning Differential Operators to Learning Algorithms

Discover how differential operators connect to machine learning algorithms in this advanced mathematical exploration by Professor Houman Owhadi from Caltech.

• YouTube
• 1 hour 39 minutes
• On-Demand
• Free Video

Piecewise Deterministic Markov Processes for Transdimensional Sampling from Flexible Bayesian Survival Models

Delve into advanced Markov processes and transdimensional sampling techniques for Bayesian survival models, exploring mathematical applications in stochastic systems and anomalous diffusion.

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

Recurrence and Transience of Multidimensional Elephant Random Walks

Delve into the mathematical analysis of multidimensional elephant random walks, exploring their recurrence and transience properties through advanced stochastic systems theory.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

Random Walk Isomorphism Theorems for a New Type of Spin System

Delve into advanced mathematical concepts exploring random walk isomorphism theorems and their applications to spin systems, presented by Dr. Swan from EPFL.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Video

Langevin Monte Carlo Beyond Lipschitz Gradient Continuity

Delve into advanced mathematical concepts of Langevin Monte Carlo methods, exploring extensions beyond traditional Lipschitz gradient continuity constraints in stochastic systems.

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

Evaluating Data Linkage: Creating Longitudinal Synthetic Data to Provide Gold-Standard Linked Datasets

Discover how to create and evaluate longitudinal synthetic datasets for population reconstruction, focusing on probabilistic data linkage methods and statistical verification techniques.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Video

High-Probability Mixing Time Bound for Gibbs Sampling from Log-Smooth Strongly Log-Concave Distributions

Delve into advanced mathematical analysis of Gibbs sampling for log-smooth strongly log-concave distributions, exploring mixing time bounds and high-probability isoperimetric inequalities in n-dimensional space.

• YouTube
• 1 hour 8 minutes
• On-Demand
• Free Video

Piecewise Deterministic Monte Carlo for Latent Variable Models - A Case Study

Explore the application and challenges of Piecewise Deterministic Monte Carlo methods in latent variable models, focusing on unbiased gradient properties and theoretical developments.

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

Geometric Functional Inequalities for Markov Chains - Mini-Course

Delve into functional-analytic approaches for analyzing Markov processes, exploring geometric inequalities and their applications in both reversible diffusion processes and discrete-time Markov chains.

• YouTube
• 2 hours 3 minutes
• On-Demand
• Free Video