18 citations · 45 across the 8 of their papers we have counts for
13 papers
ChaLearn Looking at People: Inpainting and Denoising challenges
Sergio Escalera, Marti Soler, Stephane Ayache +6
Dealing with incomplete information is a well studied problem in the context of machine learning and computational intelligence. However, in the context of computer vision, the pro…
The Indian Chefs Process
Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier +6
This paper introduces the Indian Chefs Process (ICP), a Bayesian nonparametric prior on the joint space of infinite directed acyclic graphs (DAGs) and orders that generalizes India…
Background Hardly Matters: Understanding Personality Attribution in Deep Residual Networks
Gabriëlle Ras, Ron Dotsch, Luca Ambrogioni +2
Perceived personality traits attributed to an individual do not have to correspond to their actual personality traits and may be determined in part by the context in which one enco…
Temporal Factorization of 3D Convolutional Kernels
Gabriëlle Ras, Luca Ambrogioni, Umut Güçlü +1
3D convolutional neural networks are difficult to train because they are parameter-expensive and data-hungry. To solve these problems we propose a simple technique for learning 3D…
k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport
Luca Ambrogioni, Umut Güçlü, Marcel van Gerven
Generative adversarial networks (GANs) are the state of the art in generative modeling. Unfortunately, most GAN methods are susceptible to mode collapse, meaning that they tend to…
Wasserstein variational gradient descent: From semi-discrete optimal transport to ensemble variational inference
Luca Ambrogioni, Umut Guclu, Marcel van Gerven
Particle-based variational inference offers a flexible way of approximating complex posterior distributions with a set of particles. In this paper we introduce a new particle-based…