| DeepLabCut: markerless pose estimation of user-defined body parts with deep learning A Mathis, P Mamidanna, KM Cury, T Abe, VN Murthy, MW Mathis, ... Nature neuroscience, 1, 2018 | 620 | 2018 |
| Using DeepLabCut for 3D markerless pose estimation across species and behaviors. T Nath*, A Mathis*, AC Chen, A Patel, M Bethge, MW Mathis Nature protocols 14, 2152–2176, 2019 | 186 | 2019 |
| Optimal population codes for space: Grid cells outperform place cells A Mathis, AVM Herz, M Stemmler Neural Computation 24 (9), 2280-2317, 2012 | 115 | 2012 |
| Connecting multiple spatial scales to decode the population activity of grid cells M Stemmler*, A Mathis*, AVM Herz Science Advances 1 (11), e1500816, 2015 | 107 | 2015 |
| Neuronal Representation of Social Information in the Medial Amygdala of Awake Behaving Mice Y Li, A Mathis, BF Grewe, JA Osterhout, B Ahanonu, MJ Schnitzer, ... Cell 171 (5), 1176-1190. e17, 2017 | 97 | 2017 |
| Somatosensory Cortex Plays an Essential Role in Forelimb Motor Adaptation in Mice MW Mathis, A Mathis, N Uchida Neuron 93 (6), 1493-1503. e6, 2017 | 87 | 2017 |
| Deep learning tools for the measurement of animal behavior in neuroscience MW Mathis, A Mathis Current Opinion in Neurobiology 60 (Preprint: arXiv preprint arXiv:1909.1386 …, 2020 | 57 | 2020 |
| Resolution of nested neuronal representations can be exponential in the number of neurons A Mathis, AVM Herz, MB Stemmler Physical Review Letters 109 (1), 018103, 2012 | 47 | 2012 |
| Multiscale codes in the nervous system: The problem of noise correlations and the ambiguity of periodic scales A Mathis, AVM Herz, MB Stemmler Phys. Rev. E 88 (022713), 2013 | 32 | 2013 |
| Probable nature of higher-dimensional symmetries underlying mammalian grid-cell activity patterns A Mathis, MB Stemmler, AVM Herz Elife 4, e05979, 2015 | 30 | 2015 |
| Reading out olfactory receptors: feedforward circuits detect odors in mixtures without demixing A Mathis*, D Rokni*, V Kapoor, M Bethge, VN Murthy Neuron 91 (5), 1110-23, 2016 | 29 | 2016 |
| Markerless tracking of user-defined features with deep learning A Mathis, P Mamidanna, T Abe, KM Cury, VN Murthy, MW Mathis, ... arXiv preprint arXiv:1804.03142, 2018 | 20 | 2018 |
| Pretraining boosts out-of-domain robustness for pose estimation A Mathis, T Biasi, S Schneider, M Yüksekgönül, B Rogers, M Bethge, ... Proceedings of the IEEE/CVF Winter Conference / arXiv preprint arXiv:1909.11229, 2021 | 15* | 2021 |
| On the inference speed and video-compression robustness of DeepLabCut A Mathis, RA Warren bioRxiv, doi: https://doi.org/10.1101/457242, 2018 | 15* | 2018 |
| Periodic population codes: From a single circular variable to higher dimensions, multiple nested scales, and conceptual spaces AVM Herz, A Mathis, M Stemmler Current Opinion in Neurobiology 46, 99-108, 2017 | 11 | 2017 |
| A Primer on Motion Capture with Deep Learning: Principles, Pitfalls, and Perspectives A Mathis, S Schneider, J Lauer, MW Mathis Neuron 108 (1), 44-65, 2020 | 6 | 2020 |
| Real-time, low-latency closed-loop feedback using markerless posture tracking. M Kane, G.A., Lopes, G., Sanders, J.L., Mathis, A. and Mathis Elife 9 (p.e61909.), 2020 | 4 | 2020 |
| Task-driven hierarchical deep neural networkmodels of the proprioceptive pathway KJ Sandbrink*, P Mamidanna*, C Michaelis, MW Mathis, M Bethge, ... bioRxiv, 2020 | 2 | 2020 |
| Highlights from the 29th Annual Meeting of the Society for the Neural Control of Movement A Mathis, AR Pack, RS Maeda, SD McDougle Journal of neurophysiology 122 (4), 1777-1783, 2019 | 2 | 2019 |
| The representation of space in mammals: resolution of stochastic place and grid codes A Mathis Ludwig-Maximilians-University Munich, 2012 | 2 | 2012 |
Mackenzie W. MathisSwiss Federal Institute of Technology in Lausanne (EPFL)Verified email at epfl.ch
