OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Training deep neural density estimators to identify mechanistic models of neural dynamics
Pedro J. Gonçalves, Jan-Matthis Lueckmann, Michael Deistler, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access | Times Cited: 15

Showing 15 citing articles:

sbi: A toolkit for simulation-based inference
Álvaro Tejero-Cantero, Jan Boelts, Michael Deistler, et al.
The Journal of Open Source Software (2020) Vol. 5, Iss. 52, pp. 2505-2505
Open Access | Times Cited: 186

On the Role of Theory and Modeling in Neuroscience
Daniel Levenstein, Veronica A. Alvarez, Asohan Amarasingham, et al.
Journal of Neuroscience (2023) Vol. 43, Iss. 7, pp. 1074-1088
Open Access | Times Cited: 55

Bringing Anatomical Information into Neuronal Network Models
Sacha J. van Albada, Aitor Morales-Gregorio, Timo Dickscheid, et al.
Advances in experimental medicine and biology (2021), pp. 201-234
Open Access | Times Cited: 29

Interrogating theoretical models of neural computation with emergent property inference
Sean R. Bittner, Agostina Palmigiano, Alex T. Piet, et al.
eLife (2021) Vol. 10
Open Access | Times Cited: 24

Geometric framework to predict structure from function in neural networks
Tirthabir Biswas, James E. Fitzgerald
Physical Review Research (2022) Vol. 4, Iss. 2
Open Access | Times Cited: 18

Single-neuron models linking electrophysiology, morphology and transcriptomics across cortical cell types
Anirban Nandi, Thomas Chartrand, Werner Van Geit, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 15

Interrogating theoretical models of neural computation with emergent property inference
Sean R. Bittner, Agostina Palmigiano, Alex T. Piet, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2019)
Open Access | Times Cited: 15

On Contrastive Learning for Likelihood-free Inference
Conor Durkan, Iain Murray, George Papamakarios
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 14

System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina
Cornelius Schröder, David Klindt, Sarah Strauß, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 11

Temporal derivative computation in the dorsal raphe network revealed by an experimentally-driven augmented integrate-and-fire modeling framework
Emerson F. Harkin, Michael Lynn, Alexandre Payeur, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 5

Thoughtful faces: inferring internal states across species using facial features
Alejandro Tlaie, Muad Abd El Hay, Berkutay Mert, et al.
Research Square (Research Square) (2024)
Open Access

Probabilistic solvers enable a straight-forward exploration of numerical uncertainty in neuroscience models
Jonathan Oesterle, Nicholas Krämer, Philipp Hennig, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2021)
Open Access | Times Cited: 2

Accurate Silent Synapse Estimation from Simulator-Corrected Electrophysiological Data Using the SilentMLE Python Package
Michael Lynn, Richard Naud, Jean-Claude Béı̈que
STAR Protocols (2020) Vol. 1, Iss. 3, pp. 100176-100176
Open Access | Times Cited: 1

A convolutional neural-network framework for modelling auditory sensory cells and synapses
Fotios Drakopoulos, Deepak Baby, Sarah Verhulst
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access

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