Definition: In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
Input: Within the ABC-SMC approach [1], particles are first generated from the prior distribution. Particles are then resampled from the obtained sample, and slightly perturbed. From these resampled particles, a new sample is formed, from which again particles are resampled, etc. The threshold value for the summary statistic -below which new particles are accepted -is lowered with every newly obtained sample. As a result, the acceptance rate decreases and the acceptance threshold approaches zero with an increase in the number of iterations (resamplings). Initial -values were estimated as follows. We generated 100 trees and we calculated the summary statistics (indices) and used the standard deviation of this distribution as the initial values. The -values were decreased in an exponential fashion as the sequential ABC scheme progresses. • Set the population indicator t = 1 • Set the particle indicator i = 1 • If t = 1, sample (m , θ ) from the prior π(m, θ) = π(m)π(θ|m) • If t > 1 sample m with probability π t−1 (m ) and perturb m ∼ Km t (m|m ) Sample θ from the previous population {θ(m ) t−1 } with weights w t−1 . Perturb the particle, θ ∼ KP t,m (θ|θ ) where KP t,m is the particle perturbation kernel. If π(m , θ ) = 0, repeat this step. Simulate a candidate dataset x ∼ f (x|m , θ ) If ρ(x , y) > repeat this step. 1/3

Inference of transmission network structure from HIV phylogenetic trees Supplementary information Approximate Bayesian Computation for model choice