460 citations · 1k across the 15 of their papers we have counts for
16 papers
Equivalence testing in pesticide risk assessment -- Evaluation and practical guidance for design, analysis and interpretation
Dimitry Wintermantel, Julia Osterman, Magdalena M. Mair +1
Harmful pesticide effects exceeding specific protection goals (SPG) may go undetected in underpowered experimental designs. Regulatory honeybee field studies have consistently fail…
Can predictive models be used for causal inference?
Maximilian Pichler, Florian Hartig
Supervised machine learning (ML) and deep learning (DL) algorithms excel at predictive tasks, but it is commonly assumed that they often do so by exploiting non-causal correlations…
cito: An R package for training neural networks using torch
Christian Amesoeder, Florian Hartig, Maximilian Pichler
Deep Neural Networks (DNN) have become a central method in ecology. Most current deep learning (DL) applications rely on one of the major deep learning frameworks, in particular To…
Machine Learning and Deep Learning -- A review for Ecologists
Maximilian Pichler, Florian Hartig
1. The popularity of Machine learning (ML), Deep learning (DL), and Artificial intelligence (AI) has risen sharply in recent years. Despite this spike in popularity, the inner work…
A new method for faster and more accurate inference of species associations from big community data
Maximilian Pichler, Florian Hartig
1. Joint Species Distribution models (JSDMs) explain spatial variation in community composition by contributions of the environment, biotic associations, and possibly spatially str…
Inferring species interactions using Granger causality and convergent cross mapping
Frederic Barraquand, Coralie Picoche, Matteo Detto +1
Identifying directed interactions between species from time series of their population densities has many uses in ecology. This key statistical task is equivalent to causal time se…