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Published:
Recently, together with Jose Eliel Camargo I have been exploring a very nice and simple idea. When writing scientific articles, researchers put a lot of effort collecting relevant references and placing them within their text for different puposes: to give credit, to guide the reader to other points of view, to support some statement, etc. This means that looking for papers which tend to be cited close to each other in a collection of scientific articles should provide a good way to extract a group of similar or relevant articles.
Published:
Here I review the idea of representation learning in hyperbolic space following [1-6]. I will focus on the application of these methods towards the generation of word embeddings from natural language in an unsupervised manner. The standard algorithms for generating word embeddings, such as word2vec or GloVe, generate word representations in a multidimensional Euclidean space. These have proven to be extremely useful for so called downstream tasks (such as text classification, word similarity and name entity recognition) due to their ability to capture semantic and syntactic relations among words when trained on large text corpora.
Published:
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Published in arXiv:1806.05162, 2018
We present a calculation of the NLO QCD corrections to Higgs boson pair production within the framework of a non-linearly realised Effective Field Theory in the Higgs sector, described by the electroweak chiral Lagrangian. We analyse how the NLO corrections affect distributions in the Higgs boson pair invariant mass and the transverse momentum of one of the Higgs bosons. We find that these corrections lead to significant and non-homogeneous K-factors in certain regions of the parameter space. We also provide an analytical parametrisation for the total cross-section and the mhh distribution as a function of the anomalous Higgs couplings that includes NLO corrections. Such a parametrisation can be useful for phenomenological studies.
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This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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