10 citations · 33 across the 16 of their papers we have counts for
5 papers · 1 filter
Reasoning with Neural Cellular Automata
Mayalen Etcheverry, Pietro Miotti, Aidan Sirbu +7
Modern AI architectures used to solve visual reasoning tasks typically rely heavily on global connectivity and synchronization. As biological systems demonstrate, though, sophistic…
Let It Go or Learn to Self-Correct: Continuous Diffusion for Constrained Discrete Tasks
Mariia Drozdova, Stéphane Liem Nguyen, François Fleuret
Denoising Diffusion Probabilistic Models (DDPMs) generate samples by starting from noise and repeatedly denoising while keeping each update close to the current noisy state. This b…
Diffusion as a Training Curriculum for Timestep-Free Iterative Reasoning
Mariia Drozdova, Aidan Sirbu, Pietro Miotti +4
Diffusion models and recursive reasoners are both iterative, but they carry information across iterations differently. We add a persistent hidden state to a diffusion denoiser and…
Turbo-Sim: a generalised generative model with a physical latent space
Guillaume Quétant, Mariia Drozdova, Vitaliy Kinakh +2
We present Turbo-Sim, a generalised autoencoder framework derived from principles of information theory that can be used as a generative model. By maximising the mutual information…
Generation of data on discontinuous manifolds via continuous stochastic non-invertible networks
Mariia Drozdova, Vitaliy Kinakh, Guillaume Quétant +2
The generation of discontinuous distributions is a difficult task for most known frameworks such as generative autoencoders and generative adversarial networks. Generative non-inve…