Updated README

README.md

@@ -1,5 +1,7 @@
 # NeuralEstimators
 
+![NeuralEstimators](https://github.com/msainsburydale/NeuralEstimators.jl/blob/main/logo.png?raw=true)
+
 [![][docs-dev-img]][docs-dev-url]
 [![CI](https://github.com/msainsburydale/NeuralEstimators.jl/actions/workflows/CI.yml/badge.svg)](https://github.com/msainsburydale/NeuralEstimators.jl/actions/workflows/CI.yml)
 [![codecov](https://codecov.io/gh/msainsburydale/NeuralEstimators.jl/branch/main/graph/badge.svg?token=6cXItEsKs5)](https://codecov.io/gh/msainsburydale/NeuralEstimators.jl)
@@ -16,7 +18,7 @@ A convenient interface for `R` users is available [here](https://github.com/msai
 
 ### Supporting and citing
 
-This software was developed as part of academic research. If you would like to support it, please star the repository. If you use `NeuralEstimators` in your research or other activities, please use the following citation.
+This software was developed as part of academic research. If you would like to support it, please star the repository. If you use it in your research or other activities, please use the following citation.
 
 ```
 @article{SZH_2023_neural_Bayes_estimators,
@@ -29,3 +31,15 @@ This software was developed as part of academic research. If you would like to s
 	url = {https://doi.org/10.1080/00031305.2023.2249522}
 }
 ```
+
+### Papers using NeuralEstimators
+
+- **Likelihood-Free Parameter Estimation with Neural Bayes Estimators** [[paper]](https://www.tandfonline.com/doi/full/10.1080/00031305.2023.2249522)
+Matthew Sainsbury-Dale, Andrew Zammit-Mangion, Raphaël Huser (2023)
+
+
+- **Neural Bayes Estimators for Censored Inference with Peaks-Over-Threshold Models** [[paper]](https://arxiv.org/abs/2306.15642)
+Jordan Richards, Matthew Sainsbury-Dale, Andrew Zammit-Mangion, Raphaël Huser (2023+)
+
+- **Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks** [[paper]](https://arxiv.org/abs/2310.02600)
+Matthew Sainsbury-Dale, Jordan Richards, Andrew Zammit-Mangion, Raphaël Huser (2023+)

src/missingdata.jl

@@ -142,7 +142,8 @@ function (neuralem::NeuralEM)(Z::V, θ₀::Union{Vector, Matrix, Nothing} = noth
 		θ₀ = repeat(θ₀, 1, length(Z))
 	end
 
-	estimates = Folds.map(eachindex(Z)) do i
+	# TODO should we do Folds.map() here?
+	estimates = map(eachindex(Z)) do i
 		neuralem(Z[i], θ₀[:, i]; args...)
 	end
 	estimates = hcat(estimates...)