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A gallery of up-to-date and stylish LaTeX templates, examples to help you learn LaTeX, and papers and presentations published by our community. Search or browse below.
![Phrase-Projection for Cross-Lingual JAMR training](https://writelatex.s3.amazonaws.com/published_ver/974.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240707T152349Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240707/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=21e40872da430cf5ae7841cf49b674e7672a961f5052471decf597416a7d6093)
Phrase-Projection for Cross-Lingual JAMR training
We are given spans of the target text which align to concepts in the AMR graph.These alignment do not cover every token in the target sentnce. Typically function words are not aligned to any graph fragment. Next, we obtain word alignments between the target sentence and source sentence. Since we have word alignments between target and source, and phrase alignments between target and AMR graph, we must convert the word alingments into phrase alignments. The phrases on the source side will then be projected to the AMR concepts via the target sentence
Adi Renduchinala
![Dr Driver's standard reading quiz template](https://writelatex.s3.amazonaws.com/published_ver/924.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240707T152349Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240707/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=11bff1a8d4bee3f7a557d3924a2bcc4e9dc3000c61bbdd2bee4fd67ea28d331e)
Dr Driver's standard reading quiz template
Dr Driver's standard reading quiz template, downloaded from the github gist on 20th August 2014.
The version on writeLaTeX has the commands for choosing the Meta and Meta Serif fonts commented out as these are not currently installed on the system. The template compiles with XeLaTeX.
Daniel Driver
![LaTeX Bibliography Example: The natbib Package](https://writelatex.s3.amazonaws.com/published_ver/896.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240707T152349Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240707/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=2e04acc2b9abffb913a1022a3c9804a3989f7cfc202e2e6848d57f829d8632cb)
LaTeX Bibliography Example: The natbib Package
The natbib package provides automatic numbering, sorting and formatting of in text citations and bibliographic references in LaTeX. It supports both numeric and author-year citation styles.
The natbib package is the most commonly used package for handling references in LaTeX, and it is very functional, but the more modern biblatex package is also worth a look.
writeLaTeX
![Using Open XITS Fonts with XeLaTeX](https://writelatex.s3.amazonaws.com/published_ver/11091.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240707T152349Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240707/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=7636b276fb1d102950bb371d4196ad8f6ec7758fca4a57e2e920d3b3e51d1eac)
Using Open XITS Fonts with XeLaTeX
The XITS fonts provide a Times-like serif typeface for mathematical and scientific publishing. They provide a version of the STIX fonts enriched with the OpenType MATH extension, making them suitable for high quality mathematical typesetting with XeTeX and LuaTeX. XITS fonts are free and open source.
Overleaf
![Curriculum Vitae](https://writelatex.s3.amazonaws.com/published_ver/1446.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240707T152349Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240707/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=3d9ebaf87079022ad642756ce3940ec6bc47873f37e447bfbee40f563ad64f5a)
Curriculum Vitae
"ModernCV" CV and Cover Letter
LaTeX Template
Version 1.11 (19/6/14)
This template has been downloaded from:
http://www.LaTeXTemplates.com
Original author:
Xavier Danaux (xdanaux@gmail.com)
License:
CC BY-NC-SA 3.0 (http://creativecommons.org/licenses/by-nc-sa/3.0/)
Important note:
This template requires the moderncv.cls and .sty files to be in the same
directory as this .tex file. These files provide the resume style and themes
used for structuring the document.
SouthOcean
![Royal Holloway University of London in Singapore](https://writelatex.s3.amazonaws.com/published_ver/840.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240707T152349Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240707/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=79b8216985c27e79493dbc898656db091a74ade4ec16d7331efa55dc8c57f453)
Royal Holloway University of London in Singapore
Template for written Assignments.
* bib included with examples for Harvard-Style referencing (natbib)
* Arial (?) fonts
* 1.5 spacing
Daniel Studzinski
![Lecturas de Métodos Estadísticos Multivariantes](https://writelatex.s3.amazonaws.com/published_ver/1055.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240707T152349Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240707/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=91a24f734e93922546394ad2710a36b2c4ac598134e889fa9dab66e257a51d57)
Lecturas de Métodos Estadísticos Multivariantes
Lecturas tomadas de la clase de M.Sc. Fidel Ordoñez, Carrera de Matemática UNAH, 2014
Mauricio Zelaya Aguilar
![Predictive Posterior Power for Sample Size Re-estimation](https://writelatex.s3.amazonaws.com/published_ver/874.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240707T152349Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240707/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=196004bc4556f1acfc57c73ae209201dc0bd036a53708ad9ff501c316ab9a636)
Predictive Posterior Power for Sample Size Re-estimation
Information before unblinding regarding the success of confirmatory clinical trials is highly uncertain. Estimates of expected future power which purport to use this information for purposes of sample size adjustment after given interim points need to reflect this uncertainty. Estimates of future power at later interim points need to track the evolution of the clinical trial. We employ sequential models to describe this evolution. We show that current techniques using point estimates of auxiliary parameters for estimating expected power: (i) fail to describe the range of likely power obtained after the anticipated data are observed, (ii) fail to adjust to different kinds of thresholds, and (iii) fail to adjust to the changing patient population. Our algorithms address each of these shortcomings. We show that the uncertainty arising from clinical trials is characterized by filtering later auxiliary parameters through their earlier counterparts and employing the resulting posterior distribution to estimate power. We devise MCMC-based algorithms to implement sample size adjustments after the first interim point. Bayesian models are designed to implement these adjustments in settings where both hard and soft thresholds for distinguishing the presence of treatment effects are present. Sequential MCMC-based algorithms are devised to implement accurate sample size adjustments for multiple interim points. We apply these suggested algorithms to a depression trial for purposes of illustration.
marc sobel
![Elemento Finito](https://writelatex.s3.amazonaws.com/published_ver/2068.jpeg?X-Amz-Expires=14400&X-Amz-Date=20240707T152349Z&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAWJBOALPNFPV7PVH5/20240707/us-east-1/s3/aws4_request&X-Amz-SignedHeaders=host&X-Amz-Signature=8e87e80091e988969736caa848b1df62d8600cc056fe835e1a4fec08f99771d5)
Elemento Finito
Lecturas de la clase de Elemento Finito impartida en la Carrera de Matemática de la Universidad Nacional Autónoma de Honduras
Mauricio Zelaya Aguilar