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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:

Multicore Parallel Tempering Bayeslands for Basin and Landscape Evolution
Rohitash Chandra, R. Dietmar Müller, Danial Azam, et al.
Geochemistry Geophysics Geosystems (2019) Vol. 20, Iss. 11, pp. 5082-5104
Open Access | Times Cited: 21

Showing 21 citing articles:

Bayesian geological and geophysical data fusion for the construction and uncertainty quantification of 3D geological models
Hugo K.H. Olierook, R. Scalzo, David Kohn, et al.
Geoscience Frontiers (2020) Vol. 12, Iss. 1, pp. 479-493
Open Access | Times Cited: 59
Bayesian Neural Networks via MCMC: A Python-Based Tutorial
Rohitash Chandra, Joshua A. Simmons
IEEE Access (2024) Vol. 12, pp. 70519-70549
Open Access | Times Cited: 7
Langevin-gradient parallel tempering for Bayesian neural learning
Rohitash Chandra, Konark Jain, Ratneel Deo, et al.
Neurocomputing (2019) Vol. 359, pp. 315-326
Open Access | Times Cited: 46
Cyclone trajectory and intensity prediction with uncertainty quantification using variational recurrent neural networks
Arpit Kapoor, Anshul Negi, Lucy Marshall, et al.
Environmental Modelling & Software (2023) Vol. 162, pp. 105654-105654
Open Access | Times Cited: 14
Revisiting Bayesian Autoencoders With MCMC
Rohitash Chandra, Mahir Jain, Manavendra Maharana, et al.
IEEE Access (2022) Vol. 10, pp. 40482-40495
Open Access | Times Cited: 20
Bayesreef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics
Jodie Pall, Rohitash Chandra, Danial Azam, et al.
Environmental Modelling & Software (2020) Vol. 125, pp. 104610-104610
Open Access | Times Cited: 26
Bayesian Graph Convolutional Neural Networks via Tempered MCMC
Rohitash Chandra, Ayush Bhagat, Manavendra Maharana, et al.
IEEE Access (2021) Vol. 9, pp. 130353-130365
Open Access | Times Cited: 21
Bayesian neural multi-source transfer learning
Rohitash Chandra, Arpit Kapoor
Neurocomputing (2019) Vol. 378, pp. 54-64
Closed Access | Times Cited: 23
Beyond x,y,z(t); Navigating New Landscapes of Science in the Science of Landscapes
Michèle Koppes, Leonora King
Journal of Geophysical Research Earth Surface (2020) Vol. 125, Iss. 9
Closed Access | Times Cited: 21
Gradient boosting Bayesian neural networks via Langevin MCMC
George Bai, Rohitash Chandra
Neurocomputing (2023) Vol. 558, pp. 126726-126726
Open Access | Times Cited: 7
Distributed Bayesian optimisation framework for deep neuroevolution
Rohitash Chandra, Animesh Tiwari
Neurocomputing (2021) Vol. 470, pp. 51-65
Closed Access | Times Cited: 15
Surrogate-assisted Bayesian inversion for landscape and basin evolution models
Rohitash Chandra, Danial Azam, Arpit Kapoor, et al.
Geoscientific model development (2020) Vol. 13, Iss. 7, pp. 2959-2979
Open Access | Times Cited: 14
Surrogate-assisted parallel tempering for Bayesian neural learning
Rohitash Chandra, Konark Jain, Arpit Kapoor, et al.
Engineering Applications of Artificial Intelligence (2020) Vol. 94, pp. 103700-103700
Open Access | Times Cited: 9
Hydrogeological multiple-point statistics inversion by adaptive sequential Monte Carlo
Macarena Amaya, Niklas Linde, Eric Laloy
Advances in Water Resources (2022) Vol. 166, pp. 104252-104252
Open Access | Times Cited: 5
Bayesian geological and geophysical data fusion for the construction and uncertainty quantification of 3D geological models
Hugo K.H. Olierook, R. Scalzo, David Kohn, et al.
(2019)
Open Access | Times Cited: 6
Bayesian neural networks via MCMC: a Python-based tutorial
Rohitash Chandra, Royce Chen, Joshua A. Simmons
arXiv (Cornell University) (2023)
Open Access | Times Cited: 1
Surrogate-assisted distributed swarm optimisation for computationally expensive geoscientific models
Rohitash Chandra, Yash Vardhan Sharma
Computational Geosciences (2023) Vol. 27, Iss. 6, pp. 939-954
Open Access | Times Cited: 1
Bayesreef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics
Jodie Pall, Rohitash Chandra, Danial Azam, et al.
arXiv (Cornell University) (2018)
Closed Access | Times Cited: 1
Langevin-gradient parallel tempering for Bayesian neural learning
Rohitash Chandra, Konark Jain, Ratneel Deo, et al.
arXiv (Cornell University) (2018)
Closed Access | Times Cited: 1
Surrogate-assisted parallel tempering for Bayesian neural learning
Rohitash Chandra, Konark Jain, Arpit Kapoor, et al.
arXiv (Cornell University) (2018)
Closed Access
Probabilistic modelling of sedimentary basin evolution using Bayeslands
Rohitash Chandra, Danial Azam, R. Dietmar Müller
ASEG Extended Abstracts (2019) Vol. 2019, Iss. 1, pp. 1-5
Open Access
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