Concept

Joint probability distribution

Related publications (364)

An Approach for Imitation Learning on Riemannian Manifolds

In imitation learning, multivariate Gaussians are widely used to encode robot behaviors. Such approaches do not provide the ability to properly represent end-effector orientation, as the distance metric in the space of orientations is not Euclidean. In thi ...

2017

Multi-Modal Mean-Fields via Cardinality-Based Clamping

Pascal Fua, François Fleuret

Mean Field inference is central to statistical physics. It has attracted much interest in the Computer Vision community to efficiently solve problems expressible in terms of large Conditional Random Fields. However, since it models the posterior probabilit ...

Ieee2017

Multi-Modal Mean-Fields via Cardinality-Based Clamping

Pascal Fua, François Fleuret

Ieee2017

Covariations in ecological scaling laws fostered by community dynamics

Andrea Rinaldo, Andrea Giometto, Silvia Zaoli, Amos Maritan

Scaling laws in ecology, intended both as functional relationships among ecologically relevant quantities and the probability distributions that characterize their occurrence, have long attracted the interest of empiricists and theoreticians. Empirical evi ...

2017

The Complexity of a Reliable Distributed System

Alexandre David Olivier Maurer

Studying the complexity of distributed algorithms typically boils down to evaluating how the number of messages exchanged (resp. communication steps performed or shared memory operations executed) by nodes to reliably achieve some common task, evolves with ...

2017

Characterization of input uncertainties in strategic energy planning models

Michel Bierlaire, François Maréchal, Stefano Moret, Victor Codina Gironès

Various countries and communities are defining strategic energy plans driven by concerns for climate change and security of energy supply. Energy models can support this decision-making process. The long-term planning horizon requires uncertainty to be acc ...

Elsevier Sci Ltd2017

Visualization, Adaptation, and Transformation of Procedural Grammars

Stefan Lienhard

Procedural shape grammars are powerful tools for the automatic generation of highly detailed 3D content from a set of descriptive rules. It is easy to encode variations in stochastic and parametric grammars, and an uncountable number of models can be gener ...

EPFL2017

A simulation framework for humeral head translations

Dominique Pioletti, Alexandre Terrier, Alain Farron, Philippe Müllhaupt, Ehsan Sarshari

Humeral head translations (HHT) play a crucial role in the glenohumeral (GH) joint function. The available shoulder musculoskeletal models developed based on inverse dynamics however fall short of predicting the HHT. This study aims at developing a simulat ...

Elsevier2017

MATHICSE Technical Report : Multilevel Monte Carlo approximation of functions

Fabio Nobile, Sebastian Krumscheid

Many applications across sciences and technologies require a careful quantification of non-deterministic effects to a system output, for example when evaluating the system's reliability or when gearing it towards more robust operation conditions. At the he ...

MATHICSE2017

Blind detection of polar codes

Andreas Peter Burg, Alexios Konstantinos Balatsoukas Stimming, Pascal Giard

Polar codes were recently chosen to protect the control channel information in the next-generation mobile communication standard (5G) defined by the 3GPP. As a result, receivers will have to implement blind detection of polar coded frames in order to keep ...

2017

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