David Klindt
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Neural system identification for large populations separating" what" and" where"
DA Klindt*, AS Ecker*, T Euler, M Bethge
Neural Information Processing Systems 30, 2017
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding
D Klindt*, L Schott*, Y Sharma*, I Ustyuzhaninov, W Brendel, M Bethge, ...
International Conference on Learning Representations 9, (oral presentation), 2020
Natural environment statistics in the upper and lower visual field are reflected in mouse retinal specializations
Y Qiu, Z Zhao, D Klindt, M Kautzky, KP Szatko, F Schaeffel, K Rifai, ...
Current Biology 31 (15), 3233-3247. e6, 2021
Score-based generative classifiers
RS Zimmermann, L Schott, Y Song, BA Dunn, DA Klindt
NeurIPS 2021 Workshop on Deep Generative Models and Downstream Applications, 2021
Does the way we read others' mind change over the lifespan? Insights from a massive web poll of cognitive skills from childhood to late adulthood
D Klindt, M Devaine, J Daunizeau
Cortex 86, 205-215, 2017
The temporal structure of the inner retina at a single glance
Z Zhao*, DA Klindt*, AM Chagas, KP Szatko, L Rogerson, DA Protti, ...
Scientific reports 10 (1), 1-17, 2020
A chromatic feature detector in the retina signals visual context changes
L Höfling, KP Szatko, C Behrens, Y Deng, Y Qiu, DA Klindt, Z Jessen, ...
bioRxiv, 2022.11. 30.518492, 2022
System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina
C Schröder*, D Klindt*, S Strauss, K Franke, M Bethge, T Euler, P Berens
Neural Information Processing Systems 33, (spotlight presentation), 2020
Uncovering 2-d toroidal representations in grid cell ensemble activity during 1-d behavior
E Hermansen, DA Klindt, BA Dunn
Nature Communications 15 (1), 5429, 2024
Removing inter-experimental variability from functional data in systems neuroscience
D Gonschorek, L Höfling, KP Szatko, K Franke, T Schubert, B Dunn, ...
Advances in Neural Information Processing Systems 34, 3706-3719, 2021
Efficient coding of natural scenes improves neural system identification
Y Qiu, DA Klindt, KP Szatko, D Gonschorek, L Hoefling, T Schubert, ...
PLoS computational biology 19 (4), e1011037, 2023
Iclr 2022 challenge for computational geometry & topology: Design and results
A Myers, S Utpala, S Talbar, S Sanborn, C Shewmake, C Donnat, J Mathe, ...
Topological, Algebraic and Geometric Learning Workshops 2022, 269-276, 2022
Understanding neural coding on latent manifolds by sharing features and dividing ensembles
M Bjerke, L Schott, KT Jensen, C Battistin, DA Klindt, BA Dunn
arXiv preprint arXiv:2210.03155, 2022
Controlling neural network smoothness for neural algorithmic reasoning
DA Klindt
Transactions on Machine Learning Research, 2023
Measuring Mechanistic Interpretability at Scale Without Humans
RS Zimmermann, DA Klindt, W Brendel
ICLR 2024 Workshop on Representational Alignment, 2024
Identifying Interpretable Visual Features in Artificial and Biological Neural Systems
D Klindt, S Sanborn, F Acosta, F Poitevin, N Miolane
arXiv preprint arXiv:2310.11431, 2023
Evaluation of Representational Similarity Scores Across Human Visual Cortex
F Acosta, C Conwell, S Sanborn, DA Klindt, N Miolane
UniReps: the First Workshop on Unifying Representations in Neural Models, 2023
Modelling Functional Wiring and Processing from Retinal Bipolar to Ganglion Cells
DA Klindt*, C Schröder*, A Vlasits, K Franke, P Berens, T Euler
Computational and Systems Neuroscience (Cosyne) 2021, 2021
Towards interpretable Cryo-EM: disentangling latent spaces of molecular conformations
DA Klindt, A Hyvärinen, A Levy, N Miolane, F Poitevin
Frontiers in Molecular Biosciences 11, 1393564, 2024
Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?
M Ibrahim, D Klindt, R Balestriero
arXiv preprint arXiv:2406.10743, 2024
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