Institute for Pure & Applied Mathematics (IPAM) Courses

Claire Tomlin- "Towards Real-Time Reachability"

Explore real-time reachability in high-dimensional systems, focusing on Hamilton-Jacobi PDEs, hybrid systems, and applications in traffic patterns and autonomous vehicles.

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

Generalization Theory in Machine Learning

Explore generalization theory in machine learning, covering traditional methods, deep learning, and statistical learning theory. Gain insights into overcoming the curse of dimensionality and understanding learning bounds.

• YouTube
• 1 hour 11 minutes
• On-Demand
• Free Video

Nonconvex Optimization in Matrix Optimization and Distributionally Robust Optimization

Explore nonconvex optimization in matrix and distributionally robust contexts, covering algorithms, complexity, and applications in machine learning with Stephen Wright.

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

Learning-Based Model Predictive Control - Towards Safe Learning in Control

Explores integrating learning techniques with optimization-based control for safe, high-performance systems. Discusses methods for data-driven modeling, safety filters, and constraint satisfaction in robotics applications.

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

Wasserstein Distributionally Robust Optimization - Theory and Applications in Machine Learning

Explore Wasserstein distributionally robust optimization theory and its applications in machine learning, focusing on data-driven decision-making under uncertainty and statistical learning.

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

On the Statistical Complexity of Reinforcement Learning

Explores statistical complexities in reinforcement learning, covering sample complexity, regret analysis, and off-policy evaluation. Discusses minimax-optimal approaches and function approximation in MDPs.

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

Neural Circuit Modeling of Large-Scale Brain Dynamics for Computational Psychiatry

Explore neural circuit modeling for large-scale brain dynamics in computational psychiatry, bridging microcircuit perturbations with neuroimaging biomarkers to advance personalized therapeutics.

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

Computational Contributions to Understanding Impaired Motivation and Effort in Psychosis

Exploring computational approaches to understand impaired motivation and effort in psychosis, focusing on reinforcement learning and decision-making to aid treatment development.

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

Cross-Species Translation Through Computational Analyses - Implications for Understanding and Modifying Psychiatric Treatments

Exploring computational psychiatry's impact on diagnosis, treatment, and cross-species translation in mental health, with focus on information processing and concrete examples.

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

Connectome-Based Modeling of Real World Clinical Outcomes in Addictions

Exploring connectome-based modeling to predict addiction outcomes, focusing on cocaine and opioid abstinence, network stability, and brain states. Discusses potential clinical applications and theoretical models.

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

Sensing Psychosis: Toward Robust Computational Phenotypes in Severe Mental Illness

Exploring computational approaches to quantify behavior in severe mental illnesses, aiming to develop personalized psychiatric care through unobtrusive behavioral phenotyping strategies.

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

Causality Matters in Medical Imaging

Explore causal reasoning in medical imaging, addressing data scarcity and mismatch challenges. Gain insights on predictive models, semi-supervision limitations, and strategies for successful machine learning implementation.

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

On Bayesian Models with Networks for Reconstruction and Detection

Explore Bayesian models with neural networks for MRI reconstruction and outlier detection in medical imaging, focusing on network-based priors and generative modeling approaches.

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

Geometric Understanding of Supervised and Unsupervised Deep Learning for Biomedical Image Reconstruction

Geometric understanding of deep learning for biomedical image reconstruction, exploring supervised and unsupervised approaches, with applications in various imaging modalities.

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

Deep Learning-Based MR Image Reconstruction and Contrast Conversion

Explore deep learning techniques for MR image reconstruction, parallel imaging, and contrast conversion, focusing on k-space and image space applications in medical imaging.

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