Computational Creativity 2023

Computational Creativity Lecture 22: Generative models for X (vector graphics, layouts, animation)

Computational Creativity Lecture 21: Generative models for 3D

Computational Creativity Lecture 20: 3D representations and neural radiance fields (NeRFs)

Computational Creativity Lecture 19: Generative Models for Music

Computational Creativity Lecture 18: Diffusion Developments

Computational Creativity Lecture 16: CLIP and its applications

Computational Creativity Lecture 17: DALL-E 2 and Stable Diffusion

Computational Creativity Lecture 15: Large language models and their implications

Computational Creativity Lecture 14: Attention and transformers

Computational Creativity Lecture 13: Neural language models and word embeddings

Computational Creativity Lecture 12: Normalizing flow models

Computational Creativity Lecture 11: Denoising diffusion models

Computational Creativity Lecture 10: DeepDream and neural style transfer

Computational Creativity Lecture 9: Image-to-Image GANs and GAN artists

Computational Creativity Lecture 8: Advanced GANs

Computational Creativity Lecture 7: Generative Adversarial Networks (GANs)

Computational Creativity Lecture 6: VQ-VAEs and image quality metrics

Computational Creativity Lecture 5: Variational autoencoders

Computational Creativity Lecture 4: Deep Learning Crash Course

Computational Creativity Lecture 3: Probability and machine learning review

Computational Creativity Lecture 2: Algorithms for Making Art (~1960-2010)

Computational Creativity Lecture 1: Introduction to Generative Models

Computer Vision for Visual Effects 2021

Attack the Broc 2: It Moves

Attack the Broc

Electrical, Computer, and Systems Engineering at Rensselaer

PB19: The Poisson Random Variable

PB 5: Combinatorics

PB45: The Joint Gaussian Random Variable