Tanya Schmah

1.2k total citations
25 papers, 652 citations indexed

About

Tanya Schmah is a scholar working on Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Tanya Schmah has authored 25 papers receiving a total of 652 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Statistical and Nonlinear Physics, 6 papers in Computer Vision and Pattern Recognition and 6 papers in Cognitive Neuroscience. Recurrent topics in Tanya Schmah's work include Medical Image Segmentation Techniques (4 papers), Medical Imaging Techniques and Applications (3 papers) and Nonlinear Waves and Solitons (3 papers). Tanya Schmah is often cited by papers focused on Medical Image Segmentation Techniques (4 papers), Medical Imaging Techniques and Applications (3 papers) and Nonlinear Waves and Solitons (3 papers). Tanya Schmah collaborates with scholars based in Canada, United States and Australia. Tanya Schmah's co-authors include Paul E. Rapp, A. M. Albano, Cristina Stoica, Lawrence A. Farwell, Darryl D. Holm, Steven L. Small, David Ellis, Stephen C. Strother, Geoffrey E. Hinton and Richard S. Zemel and has published in prestigious journals such as NeuroImage, Medical Physics and Neural Computation.

In The Last Decade

Tanya Schmah

23 papers receiving 629 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Tanya Schmah Canada 11 233 220 102 84 75 25 652
Eduardo Serrano Spain 16 187 0.8× 129 0.6× 132 1.3× 77 0.9× 47 0.6× 52 828
Kateřina Hlaváčková‐Schindler Austria 6 245 1.1× 134 0.6× 153 1.5× 140 1.7× 48 0.6× 21 672
L.M. Hively United States 17 401 1.7× 286 1.3× 181 1.8× 139 1.7× 82 1.1× 59 1.3k
Rafał Baranowski Poland 20 167 0.7× 207 0.9× 294 2.9× 70 0.8× 53 0.7× 135 1.7k
Temujin Gautama Belgium 12 198 0.8× 116 0.5× 105 1.0× 132 1.6× 127 1.7× 25 847
Xinbao Ning China 17 211 0.9× 196 0.9× 312 3.1× 44 0.5× 59 0.8× 70 837
Dmytro Iatsenko United Kingdom 9 261 1.1× 107 0.5× 80 0.8× 28 0.3× 174 2.3× 12 836
Peter beim Graben Germany 18 470 2.0× 208 0.9× 53 0.5× 230 2.7× 23 0.3× 52 774
Alfonso Delgado-Bonal United States 10 114 0.5× 85 0.4× 91 0.9× 78 0.9× 50 0.7× 17 612
Dean Prichard United States 9 392 1.7× 206 0.9× 216 2.1× 76 0.9× 21 0.3× 15 929

Countries citing papers authored by Tanya Schmah

Since Specialization
Citations

This map shows the geographic impact of Tanya Schmah's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tanya Schmah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tanya Schmah more than expected).

Fields of papers citing papers by Tanya Schmah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tanya Schmah. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tanya Schmah. The network helps show where Tanya Schmah may publish in the future.

Co-authorship network of co-authors of Tanya Schmah

This figure shows the co-authorship network connecting the top 25 collaborators of Tanya Schmah. A scholar is included among the top collaborators of Tanya Schmah based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tanya Schmah. Tanya Schmah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Schmah, Tanya, et al.. (2020). Exploiting Bilateral Symmetry in Brain Lesion Segmentation with Reflective Registration. 116–122. 3 indexed citations
2.
Schmah, Tanya, et al.. (2016). Performance Variability as a Predictor of Response to Aphasia Treatment. Neurorehabilitation and neural repair. 30(9). 876–882. 27 indexed citations
3.
Yourganov, Grigori, Tanya Schmah, Nathan W. Churchill, et al.. (2014). Pattern classification of fMRI data: Applications for analysis of spatially distributed cortical networks. NeuroImage. 96. 117–132. 22 indexed citations
4.
Schmah, Tanya, Laurent Risser, & François‐Xavier Vialard. (2013). Left-Invariant Metrics for Diffeomorphic Image Registration with Spatially-Varying Regularisation. Lecture notes in computer science. 16(Pt 1). 203–210. 6 indexed citations
5.
Schmah, Tanya, et al.. (2012). IMITATE: An Aphasia Treatment Motivated by Motor Cortical Connectivity. Procedia - Social and Behavioral Sciences. 61. 129–131. 3 indexed citations
6.
Schmah, Tanya, Norbert Marwan, Jesper Skovhus Thomsen, & Peter Saparin. (2011). Long range node‐strut analysis of trabecular bone microarchitecture. Medical Physics. 38(9). 5003–5011. 5 indexed citations
7.
Yourganov, Grigori, Tanya Schmah, Steven L. Small, Peter Mondrup Rasmussen, & Stephen C. Strother. (2010). Functional connectivity metrics during stroke recovery.. PubMed. 148(3). 259–70. 15 indexed citations
8.
Schmah, Tanya, Grigori Yourganov, Richard S. Zemel, et al.. (2010). Comparing Classification Methods for Longitudinal fMRI Studies. Neural Computation. 22(11). 2729–2762. 33 indexed citations
9.
Holm, Darryl D., Tanya Schmah, Cristina Stoica, & David Ellis. (2009). Geometric Mechanics and Symmetry. 107 indexed citations
10.
Schmah, Tanya, et al.. (2009). A Comparison of Classification Methods for Longitudinal fMRI Studies. NeuroImage. 47. S57–S57. 3 indexed citations
11.
Schmah, Tanya, Geoffrey E. Hinton, Steven L. Small, Stephen C. Strother, & Richard S. Zemel. (2008). Generative versus discriminative training of RBMs for classification of fMRI images. Neural Information Processing Systems. 21. 1409–1416. 42 indexed citations
12.
Schmah, Tanya & Cristina Stoica. (2006). Stability for Lagrangian relative equilibria of three-point-mass systems. Journal of Physics A Mathematical and General. 39(46). 14405–14425. 3 indexed citations
13.
Schmah, Tanya. (2006). A cotangent bundle slice theorem. Differential Geometry and its Applications. 25(1). 101–124. 5 indexed citations
14.
Roberts, Mark, Tanya Schmah, & Cristina Stoica. (2005). Relative equilibria in systems with configuration space isotropy. Journal of Geometry and Physics. 56(5). 762–779. 6 indexed citations
15.
Schmah, Tanya. (2002). Symmetries of cotangent bundles. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 4 indexed citations
16.
Rapp, Paul E., Christopher J. Cellucci, Tomas Watanabe, A. M. Albano, & Tanya Schmah. (2001). SURROGATE DATA PATHOLOGIES AND THE FALSE-POSITIVE REJECTION OF THE NULL HYPOTHESIS. International Journal of Bifurcation and Chaos. 11(4). 983–997. 29 indexed citations
17.
Schmah, Tanya. (2000). Torus actions on symplectic orbi-spaces. Proceedings of the American Mathematical Society. 129(4). 1169–1177. 1 indexed citations
18.
Rapp, Paul E., Tanya Schmah, & A.I. Mees. (1999). Models of knowing and the investigation of dynamical systems. Physica D Nonlinear Phenomena. 132(1-2). 133–149. 12 indexed citations
19.
Rapp, Paul E., A. M. Albano, Tanya Schmah, & Lawrence A. Farwell. (1993). Filtered Noise Can Mimic Low-Dimensional Chaotic Attractors. Scholarship, Research, and Creative Work at Bryn Mawr College (Bryn Mawr College). 1 indexed citations
20.
Rapp, Paul E., A. M. Albano, Tanya Schmah, & Lawrence A. Farwell. (1993). Filtered noise can mimic low-dimensional chaotic attractors. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 47(4). 2289–2297. 216 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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