Causal Representation Learning Courses and Certifications

DataLearning@ICL

Causal Representation Learning - Data Learning Seminar

Explore causal representation learning with Johann Brehmer, delving into cutting-edge techniques for understanding cause-effect relationships in data science and machine learning.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Valence Labs

BISCUIT: Causal Representation Learning from Binary Interactions

Explore causal representation learning in AI using BISCUIT method. Learn to identify causal variables from binary interactions for applications in robotics and embodied AI.

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

Valence Labs

Harnessing Geometric Signatures in Causal Representation Learning

Explore geometric signatures in causal representation learning to extract high-level latent causal factors from sensory data, leveraging interventional data without assumptions on distributions or dependencies.

• YouTube
• 1 hour 9 minutes
• On-Demand
• Free Video

Simons Institute

Causal Representation Learning: A Natural Fit for Mechanistic Interpretability

Explore how sparse shift autoencoders (SSAEs) enable accurate steering of language models by mapping embedding differences to sparse representations that capture concept shifts, offering an unsupervised approach to LLM alignment.

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

Valence Labs

A Tutorial on Causal Representation Learning

Explore Causal Representation Learning: combining machine learning with causal assumptions to identify causal variables from low-level data. Gain insights into core problems and future directions in scientific discovery.

• YouTube
• 1 hour 21 minutes
• On-Demand
• Free Video

Uncertainty in Artificial Intelligence

Causal Representation Learning - Tutorial

Explore causal representation learning, combining machine learning with causal assumptions to identify causal variables from low-level data. Gain insights into core problems and future directions in scientific discovery.

• YouTube
• 1 hour 59 minutes
• On-Demand
• Free Video

Valence Labs

Causal Discovery and Representation Learning - Day 4

Explore causal discovery and representation learning in machine learning for drug discovery with Jason Hartford's insightful presentation.

• YouTube
• 1 hour 7 minutes
• On-Demand
• Free Video

Valence Labs

Weakly Supervised Causal Representation Learning

Explore weakly supervised causal representation learning, its theoretical foundations, and practical applications in disentangling causal variables from unstructured data like images for improved causal reasoning.

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

Valence Labs

Causal Representation Learning via Soft Interventions

Explore causal representation learning through soft interventions, focusing on identifiability, prediction of intervention effects, and applications in single-cell biology using auto-encoding variational Bayes.

• YouTube
• 1 hour 14 minutes
• On-Demand
• Free Video

Uncertainty in Artificial Intelligence

Causal Representation Learning and Optimal Intervention Design

Explore causal representation learning and optimal intervention design with Caroline Uhler's insightful keynote talk at UAI 2023.

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

Broad Institute

Causal Representation Learning Through Multi-Modal Data Integration

Explore causal representation learning techniques for integrating multi-modal data in this workshop by Caroline Uhler from MIT and Broad Institute.

• YouTube
• 1 hour 17 minutes
• On-Demand
• Free Video

UC Berkeley EECS

Causal Representation Learning and Optimal Intervention Design

Explore advanced concepts in causal representation learning and intervention design, focusing on mathematical frameworks and practical applications in modern machine learning systems.

• YouTube
• 1 hour 6 minutes
• On-Demand
• Free Video

Broad Institute

Large-Scale Differentiable Causal Discovery of Factor Graphs - Lecture and Primer

Explore large-scale causal discovery using factor directed acyclic graphs and differentiable optimization. Learn about causal representation learning for genetic perturbations and combinatorial extrapolation.

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

Valence Labs

The Statistical Structure of Identifiable Generative Models

Explore the statistical structure of identifiable generative models, focusing on causal representation learning, model identifiability, and unique inferences from observations under suitable assumptions.

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

Valence Labs

Identifiability of Causal Models and Applications to Perturb-Seq Data

Explore causal model identifiability, structure learning, and applications to Perturb-seq data. Delve into interventions, latent variables, and causal disentanglement for advancing AI in drug discovery.

• YouTube
• 1 hour 12 minutes
• On-Demand
• Free Video