dsilvestro
I am a computational biologist interested in Bayesian modeling and artificial intelligence applied to evolutionary and conservation biology (among other things)
University of Fribourg
Pinned Repositories
raxmlGUI
A new graphical interface for RAxML
sampbias
Sampbias is a method and tool to 1) visualize the distribution of occurrence records and species in any user-provided dataset, 2) quantify the biasing effect of geographic features related to human accessibility, such as proximity to cities, rivers or roads, and 3) create publication-level graphs of these biasing effects in space.
fossilBM
Bayesian inference of trait evolution under a “fossilized” Brownian motion.
LiteRate
Fast estimation of immigration, birth and death rates from large datasets using reversible jump MCMC
mcmc-diversitree
This repository includes Bayesian implementations of the MuSSE and ClaSSE methods. The use of (half-Cauchy or Exponential) hyper-priors on the rate parameters allows to control for overparameterization.
npBNN
Bayesian neural networks using Numpy and Scipy
PyRate
PyRate is a program to estimate speciation, extinction, and preservation rates from fossil occurrence data using a Bayesian framework.
raxmlGUI
raxmlGUI 2.0 is now available: A new graphical interface for RAxML
rootBBB
Clade age estimation using a Bayesian Brownian bridge model
ruNNer
Train and run neural networks in Python
dsilvestro's Repositories
dsilvestro/PyRate
PyRate is a program to estimate speciation, extinction, and preservation rates from fossil occurrence data using a Bayesian framework.
dsilvestro/LiteRate
Fast estimation of immigration, birth and death rates from large datasets using reversible jump MCMC
dsilvestro/npBNN
Bayesian neural networks using Numpy and Scipy
dsilvestro/rootBBB
Clade age estimation using a Bayesian Brownian bridge model
dsilvestro/fossilBM
Bayesian inference of trait evolution under a “fossilized” Brownian motion.
dsilvestro/ruNNer
Train and run neural networks in Python
dsilvestro/mcmc-diversitree
This repository includes Bayesian implementations of the MuSSE and ClaSSE methods. The use of (half-Cauchy or Exponential) hyper-priors on the rate parameters allows to control for overparameterization.
dsilvestro/raxmlGUI
raxmlGUI 2.0 is now available: A new graphical interface for RAxML
dsilvestro/iucn_sim_dev
A program for estimating extinction probability and date for a given set of species, based on IUCN threat assessments
dsilvestro/ProvenanceFinder
Probabilistic estimation of the source of origin of sediments
dsilvestro/agez
Age estimation from zircon samples
dsilvestro/gdgt-ai
Estimation of climatic variables using GDGT data and neural networks
dsilvestro/macroevolution_practicals
dsilvestro/micro2macroEvolution
Forward individual-based simulations of evolution to link microevolutionary processes to macroevolution
dsilvestro/UMAP_scripts