David A. Klindt

According to our database, David A. Klindt authored at least 18 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders.

Charles O'Neill, David A. Klindt

CoRR, 2024

Cross-Entropy Is All You Need To Invert the Data Generating Process.

Patrik Reizinger, Alice Bizeul, Attila Juhos, Julia E. Vogt, Randall Balestriero, Wieland Brendel, David A. Klindt

CoRR, 2024

Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?

Mark Ibrahim, David A. Klindt, Randall Balestriero

CoRR, 2024

Measuring Per-Unit Interpretability at Scale Without Humans.

Roland S. Zimmermann, David A. Klindt, Wieland Brendel

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning.

Daniel Kunin, Allan Raventós, Clémentine Dominé, Feng Chen, David A. Klindt, Andrew M. Saxe, Surya Ganguli

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems.

Francisco Acosta, Fatih Dinc, William Redman, Manu S. Madhav, David A. Klindt, Nina Miolane

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Controlling Neural Network Smoothness for Neural Algorithmic Reasoning.

David A. Klindt

Trans. Mach. Learn. Res., 2023

Efficient coding of natural scenes improves neural system identification.

Yongrong Qiu, David A. Klindt, Klaudia P. Szatko, Dominic Gonschorek, Larissa Höfling, Timm Schubert, Laura Busse, Matthias Bethge, Thomas Euler

PLoS Comput. Biol., 2023

Identifying Interpretable Visual Features in Artificial and Biological Neural Systems.

David A. Klindt, Sophia Sanborn, Francisco Acosta, Frédéric Poitevin, Nina Miolane

CoRR, 2023

Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles.

Martin Bjerke, Lukas Schott, Kristopher T. Jensen, Claudia Battistin, David A. Klindt, Benjamin Adric Dunn

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results.

Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Umberto Lupo, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane

CoRR, 2022

ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results.

Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane

Proceedings of the Topological, 2022

Topological ensemble detection with differentiable yoking.

David A. Klindt, Sigurd Gaukstad, Melvin Vaupel, Erik Hermansen, Benjamin A. Dunn

Proceedings of the NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 2022

2021

Score-Based Generative Classifiers.

Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt

CoRR, 2021

Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience.

Dominic Gonschorek, Larissa Höfling, Klaudia P. Szatko, Katrin Franke, Timm Schubert, Benjamin A. Dunn, Philipp Berens, David A. Klindt, Thomas Euler

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding.

David A. Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan M. Paiton

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina.

Cornelius Schröder, David A. Klindt, Sarah Strauß, Katrin Franke, Matthias Bethge, Thomas Euler, Philipp Berens

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2017

Neural system identification for large populations separating "what" and "where".

David A. Klindt, Alexander S. Ecker, Thomas Euler, Matthias Bethge

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017