Alison P. Appling

Nature and Landscape Conservation · 2015–2019

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Nature and Landscape Conservation — 15 citations into it
• Artificial Intelligence — 12 citations into it

Whom Alison P. Appling trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. W. Viechtbauer
2. David LeBauer
3. Andrew Pullin
4. K. Treseder

Papers from Alison P. Appling's perspective

Ordered by how strongly the researchers Alison P. Appling trusts endorse each paper. Same corpus, a different order for every researcher.

1. Long Short-Term Memory
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Deep Learning
4. Learning to Forget: Continual Prediction with LSTM
5. Why Does Unsupervised Pre-training Help Deep Learning?
6. Ecological Stoichiometry: The Biology of Elements from Molecules to the Biosphere
7. Do Deep Nets Really Need to be Deep?
8. Nitrogen limitation of net primary productivity in terrestrial ecosystems is globally distributed. (Ecology)
9. Generalization of backpropagation with application to a recurrent gas market model
10. C:N:P stoichiometry in soil: is there a “Redfield ratio” for the microbial biomass?

Their papers

• Process‐Guided Deep Learning Predictions of Lake Water Temperature (2019) — 329 citations
• The metabolic regimes of flowing waters (2018) — 324 citations
• Stoichiometric flexibility in response to fertilization along gradients of environmental and organismal nutrient richness (2015) — 83 citations