arXiv Machine Learning
Deep Generative Models for Phylogenetic Inference with Complex Evolutionary Processes
Read the original on arXiv Machine Learning →The Flow has not summarised this story yet — read it at arXiv Machine Learning.
Related stories
Hugging Face Trending Papers
6d ago
Deep Generative Models for Phylogenetic Inference with Complex Evolutionary Processes
Inference of phylogenetic trees from sequences plays a central role in understanding evolutionary relationships, with applications ranging from tracking pathogen spread to reconstructing the history o...
arXiv Machine Learning
Sep 1
PhyloGFN: Phylogenetic inference with generative flow networks
arXiv:2310.08774v3 Announce Type: replace-cross Abstract: Phylogenetics is a branch of computational biology that studies the evolutionary relationships among biological entities. Its long history an...
arXiv Machine Learning
Oct 7
Algorithmically Aligned Neural Agglomerative Tree Construction
The paper introduces NN‑linkage, a neural network model that learns task‑specific merge rules for hierarchical clustering while preserving the recursive structure and efficiency of classical linkage algorithms. It aligns with the Lance‑Williams recurrence, enabling it to approximate any continuous linkage function and even implement symmetric constant‑coefficient LW recurrences exactly. Experiments on clock‑tree routing and phylogenetic reconstruction show that NN‑linkage outperforms both traditional linkage methods and other neural approaches, extending efficient hierarchical clustering to new scientific and engineering tasks.
arXiv AI
Jun 26
Simulation-based inference for rapid Bayesian parameter estimation in epidemiological models: a comparison with MCMC
arXiv:2606. 27286v1 Announce Type: new Abstract: Mechanistic epidemiological models are widely used to support infectious disease forecasting and public-health decision making.
arXiv AI
Jul 22
Approximating SPR Distance Between Phylogenetic Trees with Graph Neural Networks
arXiv:2607. 18311v1 Announce Type: cross Abstract: Comparing phylogenetic tree topologies is essential for understanding epidemic dynamics, yet biologically meaningful distances such as the Subtree Prune and Regraft (SPR) distance are NP-hard to compute and intractable on large datasets.
arXiv Machine Learning
Aug 7
Phylogenetic Tree Inference with Tropical Axial Attention
arXiv:2605. 13894v2 Announce Type: replace-cross Abstract: In this work, we introduce a Tropical Axial Attention neural reasoning architecture that replaces vanilla softmax dot-product attention with max-plus operators, inducing a piecewise-linear structure aligned with dynamic programming formulations.