Markus Marks
Cited by
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Deep-learning-based identification, tracking, pose estimation and behaviour classification of interacting primates and mice in complex environments
M Marks, Q Jin, O Sturman, L von Ziegler, S Kollmorgen, ...
Nature machine intelligence 4 (4), 331-340, 2022
Non-invasive molecularly-specific millimeter-resolution manipulation of brain circuits by ultrasound-mediated aggregation and uncaging of drug carriers
MS Ozdas, AS Shah, PM Johnson, N Patel, M Marks, TB Yasar, U Stalder, ...
Nature communications 11 (1), 4929, 2020
An optimized registration workflow and standard geometric space for small animal brain imaging
HI Ioanas, M Marks, V Zerbi, MF Yanik, M Rudin
NeuroImage 241, 118386, 2021
SAMRI—Small Animal Magnetic Resonance Imaging, November 2017
HI Ioanas, M Marks, D Schmidt, F Aymanns, M Rudin
URL https://doi. org/10.5281/zenodo 1044033, 0
Text-image alignment for diffusion-based perception
N Kondapaneni*, M Marks*, M Knott*, R Guimaraes, P Perona
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024
MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior
JJ Sun*, M Marks*, AW Ulmer, D Chakraborty, B Geuther, E Hayes, H Jia, ...
International Conference on Machine Learning (ICML), 2023
An automated open-source workflow for standards-compliant integration of small animal magnetic resonance imaging data
HI Ioanas, M Marks, CM Garin, M Dhenain, MF Yanik, M Rudin
Frontiers in neuroinformatics 14, 5, 2020
A Foundation Model for Cell Segmentation
U Israel*, M Marks*, R Dilip*, Q Li, MS Schwartz, E Pradhan, E Pao, S Li, ...
bioRxiv, 2023.11. 17.567630, 2023
Anatomically distributed neural representations of instincts in the hypothalamus
S Stagkourakis, G Spigolon, M Marks, M Feyder, J Kim, P Perona, ...
bioRxiv, 2023
A multicomponent approach to studying cultural propensities during foraging in the wild
KR Mannion, EF Ballare, M Marks, T Gruber
Journal of Animal Ecology, 2022
Robust Disentanglement of a Few Factors at a Time using rPU-VAE
B Estermann*, M Marks*, MF Yanik
Advances in Neural Information Processing Systems (NeurIPS), 2020
Predicting cardiac remodeling after myocardial infarction with machine learning: are we there yet?
SJ Reinstadler, C Dlaska, M Reindl, M Marks
International Journal of Cardiology 355, 6-7, 2022
A Closer Look at Benchmarking Self-Supervised Pre-training with Image Classification
M Marks, M Knott, N Kondapaneni, E Cole, T Defraeye, F Perez-Cruz, ...
arxiv 2407.12210, 2024
Less is More: Discovering Concise Network Explanations
N Kondapaneni, M Marks, O Mac Aodha, P Perona
ICLR 2024 Workshop on Representational Alignment, 2024
Simultaneous single-cell calcium imaging of neuronal population activity and brain-wide BOLD fMRI
RLEM Ubaghs, R Boehringer, M Marks, HK Hesse, MF Yanik, V Zerbi, ...
bioRxiv, 2023.11. 14.566368, 2023
Comparing Neural Networks and Human Subjects in Assessing Trademark Similarities
S Shimojo, FM Toma, M Noguchi, E Cole, M Marks, M Shehata, DA Wu
Journal of Vision 23 (9), 5553-5553, 2023
The Effect of Somatostatin+ Interneurons on the Negative BOLD Response.
RLEM Ubaghs, R Böhringer, M Marks, MF Yanik, BF Grewe
Shaping the BOLD signal through Excitatory and Inhibitory Interaction.
RLEM Ubaghs, H Dermutz, R Böhringer, M Marks, MF Yanik, BF Grewe
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Articles 1–18