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Scientists world-wide are putting together massive efforts to understand how the biodiversity that we see on Earth evolved from single-cell organisms at the origin of life and this diversification process is represented through the Tree of…

Populations and Evolution · Quantitative Biology 2023-12-22 Xudong Tang , Leonardo Zepeda-Nunez , Shengwen Yang , Zelin Zhao , Claudia Solis-Lemus

This paper introduces Smart-Tree, a supervised method for approximating the medial axes of branch skeletons from a tree point cloud. Smart-Tree uses a sparse voxel convolutional neural network to extract the radius and direction towards the…

Computer Vision and Pattern Recognition · Computer Science 2023-05-08 Harry Dobbs , Oliver Batchelor , Richard Green , James Atlas

The reconstruction of phylogenetic networks is an important but challenging problem in phylogenetics and genome evolution, as the space of phylogenetic networks is vast and cannot be sampled well. One approach to the problem is to solve the…

Populations and Evolution · Quantitative Biology 2023-04-14 Louxin Zhang , Niloufar Abhari , Caroline Colijn , Yufeng Wu

Phylogenetic tree reconstruction is traditionally based on multiple sequence alignments (MSAs) and heavily depends on the validity of this information bottleneck. With increasing sequence divergence, the quality of MSAs decays quickly.…

Populations and Evolution · Quantitative Biology 2011-01-11 Roland F. Schwarz , William Fletcher , Frank Förster , Benjamin Merget , Matthias Wolf , Jörg Schultz , Florian Markowetz

Extreme value statistics is the max analogue of classical statistics, while tropical geometry is the max analogue of classical geometry. In this paper, we review recent work where insights from tropical geometry were used to develop new,…

Statistics Theory · Mathematics 2022-07-22 Ngoc M Tran

Phylogenetic networks are a generalization of phylogenetic trees that allow for the representation of non-treelike evolutionary events, like recombination, hybridization, or lateral gene transfer. In this paper, we present and study a new…

Populations and Evolution · Quantitative Biology 2007-08-28 Gabriel Cardona , Francesc Rossello , Gabriel Valiente

We propose an algebraic geometric framework to study the expressivity of linear activation neural networks. A particular quantity of neural networks that has been actively studied is the number of linear regions, which gives a…

Machine Learning · Computer Science 2024-10-10 Paul Lezeau , Thomas Walker , Yueqi Cao , Shiv Bhatia , Anthea Monod

Knowing the causal structure of a system is of fundamental interest in many areas of science and can aid the design of prediction algorithms that work well under manipulations to the system. The causal structure becomes identifiable from…

Machine Learning · Statistics 2022-03-30 Martin Emil Jakobsen , Rajen D. Shah , Peter Bühlmann , Jonas Peters

Incorporating syntactic information in Neural Machine Translation models is a method to compensate their requirement for a large amount of parallel training text, especially for low-resource language pairs. Previous works on using syntactic…

Computation and Language · Computer Science 2017-11-27 Poorya Zaremoodi , Gholamreza Haffari

Given a distance matrix consisting of pairwise distances between species, a distance-based phylogenetic reconstruction method returns a tree metric or equidistant tree metric (ultrametric) that best fits the data. We investigate…

Combinatorics · Mathematics 2017-02-20 Daniel Irving Bernstein , Colby Long

Our formulation reveals that the reduction across the sequence axis can be efficiently computed in parallel through a tree reduction. Our algorithm, called Tree Attention, for parallelizing exact attention computation across multiple GPUs…

Machine Learning · Computer Science 2025-02-11 Vasudev Shyam , Jonathan Pilault , Emily Shepperd , Quentin Anthony , Beren Millidge

Program translation is an important tool to migrate legacy code in one language into an ecosystem built in a different language. In this work, we are the first to employ deep neural networks toward tackling this problem. We observe that…

Artificial Intelligence · Computer Science 2018-10-29 Xinyun Chen , Chang Liu , Dawn Song

There are several tools available to infer phylogenetic trees, which depict the evolutionary relationships among biological entities such as viral and bacterial strains in infectious outbreaks, or cancerous cells in tumor progression trees.…

Data Structures and Algorithms · Computer Science 2023-12-22 António Pedro Branco , Cátia Vaz , Alexandre P. Francisco

Phylogenetic trees and networks are leaf-labelled graphs used to model evolution. Display graphs are created by identifying common leaf labels in two or more phylogenetic trees or networks. The treewidth of such graphs is bounded as a…

Data Structures and Algorithms · Computer Science 2018-09-05 Remie Janssen , Mark Jones , Steven Kelk , Georgios Stamoulis , Taoyang Wu

We report the effects of replacing the scaled dot-product (within softmax) attention with the negative-log of Euclidean distance. This form of attention simplifies to inverse distance weighting interpolation. Used in simple one hidden layer…

Machine Learning · Computer Science 2023-12-08 Calvin McCarter

In-context learning with attention enables large neural networks to make context-specific predictions by selectively focusing on relevant examples. Here, we adapt this idea to supervised learning procedures such as lasso regression and…

Machine Learning · Statistics 2025-12-11 Erin Craig , Robert Tibshirani

Exponential families are widely used in machine learning; they include many distributions in continuous and discrete domains (e.g., Gaussian, Dirichlet, Poisson, and categorical distributions via the softmax transformation). Distributions…

Ultametrics are an important class of distances used in applications such as phylogenetics, clustering and classification theory. Ultrametrics are essentially distances that can be represented by an edge-weighted rooted tree so that all of…

Combinatorics · Mathematics 2026-02-13 Katharina T. Huber , Vincent Moulton , Guillaume E. Scholz

Attention Residuals replace standard additive residual connections with learned softmax attention over previous layer outputs, enabling selective cross-layer routing. However, standard Attention Residuals still attend over cumulative hidden…

Machine Learning · Computer Science 2026-05-20 Cheng Luo , Zefan Cai , Junjie Hu

The tropical semiring is an algebraic system with addition ``$\max$'' and multiplication ``$+$''. As well as in conventional algebra, linear programming in the tropical semiring has been developed. In this study, we introduce a new type of…

Optimization and Control · Mathematics 2026-02-03 Yuki Nishida