732 citations · 778 across the 6 of their papers we have counts for
6 papers
Art and the science of generative AI: A deeper dive
Ziv Epstein, Aaron Hertzmann, Laura Herman +11
A new class of tools, colloquially called generative AI, can produce high-quality artistic media for visual arts, concept art, music, fiction, literature, video, and animation. The…
Learning to See: You Are What You See
Memo Akten, Rebecca Fiebrink, Mick Grierson
The authors present a visual instrument developed as part of the creation of the artwork Learning to See. The artwork explores bias in artificial neural networks and provides mecha…
Deep Meditations: Controlled navigation of latent space
Memo Akten, Rebecca Fiebrink, Mick Grierson
We introduce a method which allows users to creatively explore and navigate the vast latent spaces of deep generative models. Specifically, our method enables users to \textit{disc…
Calligraphic Stylisation Learning with a Physiologically Plausible Model of Movement and Recurrent Neural Networks
Daniel Berio, Memo Akten, Frederic Fol Leymarie +2
We propose a computational framework to learn stylisation patterns from example drawings or writings, and then generate new trajectories that possess similar stylistic qualities. W…
Collaborative creativity with Monte-Carlo Tree Search and Convolutional Neural Networks
Memo Akten, Mick Grierson
We investigate a human-machine collaborative drawing environment in which an autonomous agent sketches images while optionally allowing a user to directly influence the agent's tra…
Real-time interactive sequence generation and control with Recurrent Neural Network ensembles
Memo Akten, Mick Grierson
Recurrent Neural Networks (RNN), particularly Long Short Term Memory (LSTM) RNNs, are a popular and very successful method for learning and generating sequences. However, current g…