Generative Models Courses and Certifications

Outlier

Diffusion Models - Paper Explanation - Math Explained

Comprehensive explanation of diffusion models, covering theory, architecture, math derivation, algorithms, improvements, and results. Includes comparisons to other methods and references to state-of-the-art applications.

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

Outlier

VQ-GAN - PyTorch Implementation

Implement Vector Quantized Generative Adversarial Networks (VQGAN) using PyTorch, covering encoder, decoder, codebook, discriminator, and transformer stages for high-resolution image synthesis.

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

Bolei Zhou

Human-Centric AI for Computer Vision and Machine Autonomy - ICCV'21 Tutorial

Explore human-centric AI in computer vision, covering explainable models, interpretable neural networks, and interactive machine learning for improved AI systems and autonomous machines.

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

Bolei Zhou

Towards Falsifiable Interpretability Research in Machine Learning - Lecture

Explore techniques for falsifiable interpretability in machine learning, focusing on saliency, individual neurons, and populations. Learn to build stronger hypotheses for more robust research.

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

Bolei Zhou

Interpreting Deep Generative Models for Interactive AI Content Creation

Explore deep generative models for AI content creation, covering image generation, latent space manipulation, and interactive techniques. Learn about challenges and applications in this cutting-edge field.

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

Simons Institute

Sample-Complexity of Estimating Convolutional and Recurrent Neural Networks

Explore sample-complexity in estimating neural networks, focusing on CNN and RNN architectures. Learn about generative models, minimax analysis, and key results through theoretical proofs and practical experiments.

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

Simons Institute

Generative Models

Explore generative models in deep learning, covering theoretical perspectives, hacker models, information flow, and provable algorithms for learning classifiers and phylogenetic reconstruction.

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

Simons Institute

Planning and Markov Decision Processes - Part 2

Explore advanced concepts in reinforcement learning, including generative models, sample complexity, value equations, and linear programming, with experts from leading institutions.

• YouTube
• 1 hour 13 minutes
• On-Demand
• Free Video

Alexander Amini;  MIT

Deep Generative Modeling

Explore deep generative modeling, including autoencoders, VAEs, and GANs. Learn about latent variables, representation learning, and applications in image generation and domain transformation.

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

Alexander Amini;  MIT

Beyond Deep Learning - Learning+Reasoning

Explore advanced AI concepts beyond deep learning, focusing on integrating reasoning with learning for more robust and interpretable systems in this IBM Research lecture.

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

Alexander Amini;  MIT

Introduction to Deep Learning - MIT 2018

Explore foundations of deep learning, including perceptrons, neural networks, loss functions, and optimization techniques. Gain insights into training challenges and strategies for effective model development.

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

Alan Turing Institute

Optimal Transport for Machine Learning - Gabriel Peyre, Ecole Normale Superieure

Explore optimal transport in machine learning, covering Kantorovitch's formulation, entropic regularization, and applications in generative models and GANs. Gain insights into cutting-edge advances in data science.

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

Alan Turing Institute

Exploring the Cosmos with Deep Learning

Explore how deep learning revolutionizes cosmology, from detecting gravitational lenses to generating galaxy images and modeling cosmic structures, addressing challenges in modern astronomical surveys.

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

Alfredo Canziani

Unsupervised Learning - Autoencoding the Targets

Explore unsupervised learning and generative models, covering topics like latent space interpolation, style transfer, super resolution, and autoencoders. Gain insights into advanced machine learning concepts and techniques.

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

Valerio Velardo - The Sound of AI

From Autoencoders to Variational Autoencoders - Improving the Encoder

Explore the transformation from autoencoders to variational autoencoders, focusing on improved encoding using multivariate normal distributions for enhanced generative capabilities in AI and sound processing.

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