Institute for Pure & Applied Mathematics (IPAM) Courses

Constrained Multimodal Data Mining Using Coupled Matrix and Tensor Factorizations

Explore advanced techniques for analyzing complex multimodal data using coupled matrix and tensor factorizations. Learn about extracting insights from heterogeneous datasets in metabolomics and neuroscience.

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

Interpreting Deep Neural Networks Towards Trustworthiness - IPAM at UCLA

Explore techniques for interpreting deep neural networks, including ACD and AWD methods, to enhance trustworthiness in AI applications across scientific domains.

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

Explainable AI to Analyze Internal Decision Mechanism of Deep Neural Networks

Explore techniques for understanding and improving deep neural networks' decision-making processes, focusing on safety in critical applications and automatic correction of unreliable internal nodes.

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

Multiview and Self-Supervised Representation Learning - Nonlinear Mixture Identification

Explore nonlinear mixture identification in multiview and self-supervised representation learning. Gain insights into extracting essential information from high-dimensional data for improved AI applications.

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

From Network Dissection to Policy Dissection - Emergent Concepts in Deep Representations

Explore emergent concepts in deep neural networks, from image classification to reinforcement learning, revealing inner workings and enabling meaningful human-AI interactions for content creation and robotics control.

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

AI for the Sciences - Recent Developments for XAI - IPAM at UCLA

Explore recent advancements in Explainable AI for scientific applications, focusing on novel insights and developments presented by Klaus-Robert Müller at IPAM's workshop.

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

Learning-Based Low-Rank Approximations - IPAM at UCLA

Explores learning-based algorithms for low-rank matrix approximation, focusing on optimizing sketching matrices using training data to significantly reduce approximation errors in efficient computational methods.

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

Spectral Decomposition of Atomic Structures in Heterogeneous Cryo-EM

Innovative approach to recover 3D atomic structures of flexible macromolecules from cryo-EM data, combining biological knowledge with spectral analysis to estimate conformational variations.

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

New Approaches in Simulation of Transition Paths - IPAM at UCLA

Explores tensor methods for simulating chemical transition processes, focusing on compressing high-dimensional PDE functions and introducing a novel tensor-network generative modeling approach without optimization.

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

Inference Poses for Reconstruction of 3D Molecular Volumes from Cryo-EM Images

Explore innovative techniques for reconstructing 3D molecular structures from cryo-EM data, focusing on the cryoAI algorithm that combines machine learning and physics-based approaches for efficient processing of large datasets.

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

Recovering Small Molecular Structures Using Cryo-EM - IPAM at UCLA

Explores innovative computational frameworks for recovering small molecular structures using cryo-EM, challenging conventional limitations and bypassing particle picking for enhanced structural determination.

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

Molecular Structure Extrapolation to Zero Dose with CryoEM - IPAM at UCLA

Explore zero-dose extrapolation in cryoEM, enhancing structural detail and insights into radiation damage for improved molecular visualization and atomic model refinement.

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

Approaches for Exploring the Geometry of Molecular Conformations in Cryo-EM

Explore advanced techniques for analyzing molecular conformations in cryo-electron microscopy, focusing on emerging approaches for complex conformational heterogeneity and associated challenges.

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

Machine Learning for Determining Protein Structure and Dynamics from Cryo-EM Images

Explore machine learning techniques for analyzing cryo-EM images to determine protein structure and dynamics, focusing on the cryoDRGN algorithm and its applications in structural biology.

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

Contextual Conformational Variability in CryoEM and CryoET Using Deep Learning

Explore deep learning methodologies for analyzing CryoEM and CryoET data, focusing on population dynamics and contextual annotation of macromolecules in cellular environments.

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