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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.

FSU-MATH2400-Project2
This is a project for Calculus 2 students at Fitchburg State University. This project walks students through two examples of using definite integrals to determine the volume of objects: a bundt cake serves as the solid of revolution and the students build a structure from play dough that is not a solid of revolution.
Sarah Wright

ALUNO(S) - TCC I FAPI
Modelo LaTex para preparação do documento final de Monografia TCC
O modelo está em conformidade com ABNT NBR
Faculdade do Piaui
Sahra Karolina, Alexandre Tolstenko

Elsevier Article (elsarticle) Template
Template for submissions to Elsevier journals using the elsarticle.cls (v3.3) document class.
Please use and set your project's main document to one of the following, depending on the citation scheme you need:
elsarticle-template-num.tex, template file for numerical citations
elsarticle-template-harv.tex, template file for name-year citations
elsarticle-template-num-names.tex, template file for numerical
citations + new natbib option. Eg. Jones et al. [21]
Elsevier

UNM Ph.D. Proposal and Dissertation Templates
University of New Mexico templates for proposal and dissertation.
Jeremy Benson

MSC thesis University of Southampton 2019
Master dissertation thesis template for master students
Shouyu Xie

ejerciciosBachi
Plantilla para crear ejercicios
Pablo

ARML Lecture: Telescoping Series and Sums
An introduction to Telescoping Series and Sums.
Justin Stevens

Conservative Wasserstein Training for Pose Estimation
Paper presented at ICCV 2019.
This paper targets the task with discrete and periodic
class labels (e.g., pose/orientation estimation) in the context of deep learning. The commonly used cross-entropy or
regression loss is not well matched to this problem as they
ignore the periodic nature of the labels and the class similarity, or assume labels are continuous value. We propose to
incorporate inter-class correlations in a Wasserstein training framework by pre-defining (i.e., using arc length of a
circle) or adaptively learning the ground metric. We extend
the ground metric as a linear, convex or concave increasing
function w.r.t. arc length from an optimization perspective.
We also propose to construct the conservative target labels
which model the inlier and outlier noises using a wrapped
unimodal-uniform mixture distribution. Unlike the one-hot
setting, the conservative label makes the computation of
Wasserstein distance more challenging. We systematically
conclude the practical closed-form solution of Wasserstein
distance for pose data with either one-hot or conservative
target label. We evaluate our method on head, body, vehicle and 3D object pose benchmarks with exhaustive ablation studies. The Wasserstein loss obtaining superior performance over the current methods, especially using convex mapping function for ground metric, conservative label,
and closed-form solution.
Xiaofeng Liu, Yang Zou, Tong Che, Peng Ding, Ping Jia, Jane You, B.V.K. Vijaya Kumar

Reseña del Autor del premio Nobel
Reseña del Autor del premio Nobel
Wendy Tamayo