7 citations · 24 across the 7 of their papers we have counts for
8 papers
Neural Cellular Automata Manifold
Alejandro Hernandez Ruiz, Armand Vilalta, Francesc Moreno-Noguer
Very recently, the Neural Cellular Automata (NCA) has been proposed to simulate the morphogenesis process with deep networks. NCA learns to grow an image starting from a fixed sing…
Feature discriminativity estimation in CNNs for transfer learning
Victor Gimenez-Abalos, Armand Vilalta, Dario Garcia-Gasulla +2
The purpose of feature extraction on convolutional neural networks is to reuse deep representations learnt for a pre-trained model to solve a new, potentially unrelated problem. Ho…
A Visual Distance for WordNet
Raquel Pérez-Arnal, Armand Vilalta, Dario Garcia-Gasulla +3
Measuring the distance between concepts is an important field of study of Natural Language Processing, as it can be used to improve tasks related to the interpretation of those sam…
Full-Network Embedding in a Multimodal Embedding Pipeline
Armand Vilalta, Dario Garcia-Gasulla, Ferran Parés +4
The current state-of-the-art for image annotation and image retrieval tasks is obtained through deep neural networks, which combine an image representation and a text representatio…
Building Graph Representations of Deep Vector Embeddings
Dario Garcia-Gasulla, Armand Vilalta, Ferran Parés +5
Patterns stored within pre-trained deep neural networks compose large and powerful descriptive languages that can be used for many different purposes. Typically, deep network repre…
An Out-of-the-box Full-network Embedding for Convolutional Neural Networks
Dario Garcia-Gasulla, Armand Vilalta, Ferran Parés +5
Transfer learning for feature extraction can be used to exploit deep representations in contexts where there is very few training data, where there are limited computational resour…
Fluid Communities: A Competitive, Scalable and Diverse Community Detection Algorithm
Ferran Parés, Dario Garcia-Gasulla, Armand Vilalta +5
We introduce a community detection algorithm (Fluid Communities) based on the idea of fluids interacting in an environment, expanding and contracting as a result of that interactio…
On the Behavior of Convolutional Nets for Feature Extraction
Dario Garcia-Gasulla, Ferran Parés, Armand Vilalta +5
Deep neural networks are representation learning techniques. During training, a deep net is capable of generating a descriptive language of unprecedented size and detail in machine…