Search Results for author: Memo Akten

Found 5 papers, 0 papers with code

Learning to See: You Are What You See

no code implementations28 Feb 2020 Memo Akten, Rebecca Fiebrink, Mick Grierson

The exploration of these representations acts as a metaphor for the process of developing a visual understanding and/or visual vocabulary of the world.

Deep Meditations: Controlled navigation of latent space

no code implementations27 Feb 2020 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.

Navigate

Calligraphic Stylisation Learning with a Physiologically Plausible Model of Movement and Recurrent Neural Networks

no code implementations24 Sep 2017 Daniel Berio, Memo Akten, Frederic Fol Leymarie, Mick Grierson, Réjean Plamondon

We propose a computational framework to learn stylisation patterns from example drawings or writings, and then generate new trajectories that possess similar stylistic qualities.

Collaborative creativity with Monte-Carlo Tree Search and Convolutional Neural Networks

no code implementations14 Dec 2016 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 trajectory.

Real-time interactive sequence generation and control with Recurrent Neural Network ensembles

no code implementations14 Dec 2016 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.

Continuous Control

Cannot find the paper you are looking for? You can Submit a new open access paper.