Automatic differentiation

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Related publications (29)

Robust Distributed Learning

El Mahdi El Mhamdi

Whether it occurs in artificial or biological substrates, {\it learning} is a {distributed} phenomenon in at least two aspects. First, meaningful data and experiences are rarely found in one location, hence {\it learners} have a strong incentive to work t ...

EPFL2020

MPGM: Scalable and Accurate Multiple Network Alignment

Matthias Grossglauser, Ehsan Kazemi

Protein-protein interaction (PPI) network alignment is a canonical operation to transfer biological knowledge among species. The alignment of PPI-networks has many applications, such as the prediction of protein function, detection of conserved network mot ...

IEEE COMPUTER SOC2020

Approaching Ontology Alignment through Representation Learning to Bridge the Semantic Gap in Engineering Applications

Prodromos Kolyvakis

The current information landscape is characterised by a vast amount of relatively semantically homogeneous, when observed in isolation, data silos that are, however, drastically semantically fragmented when considered as a whole. Within each data silo, inf ...

EPFL2020

What is Trending on Wikipedia? Capturing Trends and Language Biases Across Wikipedia Editions

Pierre Vandergheynst, Nicolas Aspert, Volodymyr Miz, Benjamin Ricaud, Joëlle Hanna

In this work, we propose an automatic evaluation and comparison of the browsing behavior of Wikipedia readers that can be applied to any language editions of Wikipedia. As an example, we focus on English, French, and Russian languages during the last four ...

ACM2020

Biologically plausible deep learning – but how far can we go with shallow networks?

Wulfram Gerstner, Johanni Michael Brea, Bernd Albert Illing

Training deep neural networks with the error backpropagation algorithm is considered implausible from a biological perspective. Numerous recent publications suggest elaborate models for biologically plausible variants of deep learning, typically defining s ...

2019

The morning commute in urban areas with heterogeneous trip lengths

Nikolaos Geroliminis, Raphael Ali Francis Lamotte

This paper investigates the equilibrium properties of the morning commute problem at the network level with heterogeneous trip lengths. Congestion is modeled with a Macroscopic Fundamental Diagram relating the space-mean speed of a network to the vehicular ...

2018

The morning commute in urban areas with heterogeneous trip lengths

Nikolaos Geroliminis, Raphael Ali Francis Lamotte

2017

Fréchet means in Wasserstein space : theory and algorithms

Yoav Zemel

This work studies the problem of statistical inference for Fréchet means in the Wasserstein space of measures on Euclidean spaces,

\mathcal W_2 ( \mathbb R^d )

. This question arises naturally from the problem of separating amplitude and phase variation i ...

EPFL2017

Automated Classification of Brain Tumor Type in Whole-Slide Digital Pathology Images Using Local Representative Tiles

Adrien Raphaël Depeursinge

Computerized analysis of digital pathology images offers the potential of improving clinical care (e.g. automated diagnosis) and catalyzing research (e.g. discovering disease subtypes). There are two key challenges thwarting computerized analysis of digita ...

Elsevier2016

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