Catégorie
Statistique bayésienne
Publications associées (535)
Discovering Tonal Profiles with Latent Dirichlet Allocation
Martin Alois Rohrmeier, Fabian Claude Moss
Music analysis, in particular harmonic analysis, is concerned with the way pitches are organized in pieces of music, and a range of empirical applications have been developed, for example, for chord recognition or key finding. Naturally, these approaches r ...
2021Network Classifiers Based On Social Learning
Ali H. Sayed, Stefan Vlaski, Virginia Bordignon
This work proposes a new way of combining independently trained classifiers over space and time. Combination over space means that the outputs of spatially distributed classifiers are aggregated. Combination over time means that the classifiers respond to ...
IEEE2021Context-Aware Image Super-Resolution Using Deep Neural Networks
Image super-resolution is a classic ill-posed computer vision and image processing problem, addressing the question of how to reconstruct a high-resolution image from its low-resolution counterpart. Current state-of-the-art methods have improved the perfor ...
EPFL2021Distributionally Robust Optimization with Markovian Data
Daniel Kuhn, Mengmeng Li, Tobias Sutter
We study a stochastic program where the probability distribution of the uncertain problem parameters is unknown and only indirectly observed via finitely many correlated samples generated by an unknown Markov chain with d states. We propose a data-driven d ...
2021Uncertain Sampling with Certain Priors
Sampling has always been at the heart of signal processing providing a bridge between the analogue world and discrete representations of it, as our ability to process data in continuous space is quite limited. Furthermore, sampling plays a key part in unde ...
EPFL2021Product of experts for robot learning from demonstration
Adaptability and ease of programming are key features necessary for a wider spread of robotics in factories and everyday assistance. Learning from demonstration (LfD) is an approach to address this problem. It aims to develop algorithms and interfaces such ...
EPFL2021Learning Constrained Distributions of Robot Configurations with Generative Adversarial Network
Sylvain Calinon, Julius Maximilian Jankowski, Emmanuel Pignat, Teguh Santoso Lembono
In high dimensional robotic system, the manifold of the valid configuration space often has a complex shape, especially under constraints such as end-effector orientation or static stability. We propose a generative adversarial network approach to learn th ...
IEEE2021Exploring the foundations of tonality: statistical cognitive modeling of modes in the history of Western classical music
Martin Alois Rohrmeier, Fabian Claude Moss, Daniel Harasim
Tonality is one of the most central theoretical concepts for the analysis of Western classical music. This study presents a novel approach for the study of its historical development, exploring in particular the concept of mode. Based on a large dataset of ...
SPRINGERNATURE2021Common Information Components Analysis
Michael Christoph Gastpar, Erixhen Sula
Wyner's common information is a measure that quantifies and assesses the commonality between two random variables. Based on this, we introduce a novel two-step procedure to construct features from data, referred to as Common Information Components Analysis ...
MDPI2021Work fluctuations in the active Ornstein-Uhlenbeck particle model
We study the large deviations of the power injected by the active force for an active Ornstein-Uhlenbeck particle (AOUP), free or in a confining potential. For the free-particle case, we compute the rate function analytically in d-dimensions from a saddle- ...
IOP Publishing Ltd2021