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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:

Intrinsic noise improves speech recognition in a computational model of the auditory pathway
Achim Schilling, Richard Gerum, Alexandra Zankl, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

The stochastic resonance model of auditory perception: A unified explanation of tinnitus development, Zwicker tone illusion, and residual inhibition
Achim Schilling, Konstantin Tziridis, Holger Schulze, et al.
Progress in brain research (2021), pp. 139-157
Open Access | Times Cited: 47
Known operator learning and hybrid machine learning in medical imaging—a review of the past, the present, and the future
Andreas Maier, Harald Köstler, Marco Heisig, et al.
Progress in Biomedical Engineering (2022) Vol. 4, Iss. 2, pp. 022002-022002
Open Access | Times Cited: 27
Analysis and visualization of sleep stages based on deep neural networks
Patrick Krauß, Claus Metzner, Nidhi Joshi, et al.
Neurobiology of Sleep and Circadian Rhythms (2021) Vol. 10, pp. 100064-100064
Open Access | Times Cited: 32
Analysis of continuous neuronal activity evoked by natural speech with computational corpus linguistics methods
Achim Schilling, Rosario Tomasello, Malte R. Henningsen‐Schomers, et al.
Language Cognition and Neuroscience (2020) Vol. 36, Iss. 2, pp. 167-186
Open Access | Times Cited: 29
Neural network based formation of cognitive maps of semantic spaces and the putative emergence of abstract concepts
Paul Stoewer, Achim Schilling, Andreas Maier, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 9
Deep learning based decoding of single local field potential events
Achim Schilling, Richard Gerum, Claudia Boehm, et al.
NeuroImage (2024) Vol. 297, pp. 120696-120696
Open Access | Times Cited: 3
Neural network based successor representations to form cognitive maps of space and language
Paul Stoewer, Christian Schlieker, Achim Schilling, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 15
Simulated transient hearing loss improves auditory sensitivity
Patrick Krauß, Konstantin Tziridis
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 18
Dynamics and Information Import in Recurrent Neural Networks
Claus Metzner, Patrick Krauß
Frontiers in Computational Neuroscience (2022) Vol. 16
Open Access | Times Cited: 12
When Noise meets Chaos: Stochastic Resonance in Neurochaos Learning
N B Harikrishnan, Nithin Nagaraj
Neural Networks (2021) Vol. 143, pp. 425-435
Open Access | Times Cited: 15
Integration of Leaky-Integrate-and-Fire Neurons in Standard Machine Learning Architectures to Generate Hybrid Networks: A Surrogate Gradient Approach
Richard Gerum, Achim Schilling
Neural Computation (2021) Vol. 33, Iss. 10, pp. 2827-2852
Open Access | Times Cited: 14
Deep Neural Network Model of Hearing-Impaired Speech-in-Noise Perception
Stephanie Haro, Christopher J. Smalt, Gregory Ciccarelli, et al.
Frontiers in Neuroscience (2020) Vol. 14
Open Access | Times Cited: 14
Neural correlates of linguistic collocations during continuous speech perception
Armine Garibyan, Achim Schilling, Claudia Boehm, et al.
Frontiers in Psychology (2022) Vol. 13
Open Access | Times Cited: 8
Control of noise-induced coherent oscillations in three-neuron motifs
Florian Bönsel, Patrick Krauß, Claus Metzner, et al.
Cognitive Neurodynamics (2021) Vol. 16, Iss. 4, pp. 941-960
Open Access | Times Cited: 11
Transforming English language learning: Advanced speech recognition with MLP-LSTM for personalized education
Myagmarsuren Orosoo, Namjildagva Raash, Mark Treve, et al.
Alexandria Engineering Journal (2024) Vol. 111, pp. 21-32
Open Access | Times Cited: 1
The Stochastic Resonance model of auditory perception: A unified explanation of tinnitus development, Zwicker tone illusion, and residual inhibition
Achim Schilling, Konstantin Tziridis, Holger Schulze, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 11
Deep learning based decoding of local field potential events
Achim Schilling, Richard Gerum, Claudia Boehm, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 7
Analysis and Visualization of Sleep Stages based on Deep Neural Networks
Patrick Krauß, Claus Metzner, Nidhi Joshi, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 7
Neural Correlates of Linguistic Collocations During Continuous Speech Perception
Armine Garibyan, Achim Schilling, Claudia Boehm, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 4
Analysis of continuous neuronal activity evoked by natural speech with computational corpus linguistics methods
Achim Schilling, Rosario Tomasello, Malte R. Henningsen‐Schomers, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2020)
Open Access | Times Cited: 4
Comparing the Robustness of Classical and Deep Learning Techniques for Text Classification
Quynh Tran, Krystsina Shpileuskaya, Elaine Zaunseder, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2022), pp. 1-10
Closed Access | Times Cited: 3
A toy model for the auditory system that exploits stochastic resonance
Francesco Veronesi, E. Milotti
European Journal of Physics (2021) Vol. 43, Iss. 2, pp. 025703-025703
Open Access | Times Cited: 3
Dynamical Phases and Resonance Phenomena in Information-Processing Recurrent Neural Networks
Claus Metzner, Patrick Krauß
arXiv (Cornell University) (2021)
Open Access | Times Cited: 2
Research on vehicle speech recognition algorithm based on multidimensional data
Zengxi Wang, Xia Pan, Yan Zong
(2023), pp. 13-13
Closed Access
Spiking Machine Intelligence: What we can learn from biology and how spiking Neural Networks can help to improve Machine Learning
Richard Gerum, Achim Schilling
arXiv (Cornell University) (2020)
Closed Access
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