David A. Klindt

34 papers A* 9Journal 21Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Causality is Key for Interpretability Claims to Generalise. CoRR Shruti Joshi, Aaron Mueller, David A. Klindt, Wieland Brendel, Patrik Reizinger, Dhanya Sridhar
2026	J	`jnl`	FederatedFactory: Generative One-Shot Learning for Extremely Non-IID Distributed Scenarios. CoRR Andrea Moleri, Christian Internò, Ali Raza, Markus Olhofer, David A. Klindt, Fabio Stella, Barbara Hammer
2026	J	`jnl`	Stop Probing, Start Coding: Why Linear Probes and Sparse Autoencoders Fail at Compositional Generalisation. CoRR Vitória Barin Pacela, Shruti Joshi, Isabela Camacho, Simon Lacoste-Julien, David A. Klindt
2026	J	`jnl`	The Observer Effect in World Models: Invasive Adaptation Corrupts Latent Physics. CoRR Christian Internò, Jumpei Yamaguchi, Loren Amdahl-Culleton, Markus Olhofer, David A. Klindt, Barbara Hammer
2025	J	`jnl`	AI-Generated Video Detection via Perceptual Straightening. CoRR Christian Internò, Robert Geirhos, Markus Olhofer, Sunny Liu, Barbara Hammer, David A. Klindt
2025	J	`jnl`	An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research. CoRR Patrik Reizinger, Randall Balestriero, David A. Klindt, Wieland Brendel
2025	A*	`conf`	Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders. ICML Charles O'Neill, Alim Gumran, David A. Klindt
2025	A*	`conf`	Cross-Entropy Is All You Need To Invert the Data Generating Process. ICLR Patrik Reizinger, Alice Bizeul, Attila Juhos, Julia E. Vogt, Randall Balestriero, Wieland Brendel, David A. Klindt
2025	J	`jnl`	DIET-CP: Lightweight and Data Efficient Self Supervised Continued Pretraining. CoRR Bryan Rodas, Natalie Montesino, Jakob Ambsdorf, David A. Klindt, Randall Balestriero
2025	J	`jnl`	From superposition to sparse codes: interpretable representations in neural networks. CoRR David A. Klindt, Charles O'Neill, Patrik Reizinger, Harald Maurer, Nina Miolane
2025	J	`jnl`	Occam's Razor for SSL: Memory-Efficient Parametric Instance Discrimination. Trans. Mach. Learn. Res. Eric Gan, Patrik Reizinger, Alice Bizeul, Attila Juhos, Mark Ibrahim, Randall Balestriero, David A. Klindt, Wieland Brendel, Baharan Mirzasoleiman
2025	—	`conf`	Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research. ICML (Position Papers) Patrik Reizinger, Randall Balestriero, David A. Klindt, Wieland Brendel
2024	J	`jnl`	Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders. CoRR Charles O'Neill, David A. Klindt
2024	J	`jnl`	Cross-Entropy Is All You Need To Invert the Data Generating Process. CoRR Patrik Reizinger, Alice Bizeul, Attila Juhos, Julia E. Vogt, Randall Balestriero, Wieland Brendel, David A. Klindt
2024	A*	`conf`	Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning. NeurIPS Daniel Kunin, Allan Raventós, Clémentine C. J. Dominé, Feng Chen, David A. Klindt, Andrew M. Saxe, Surya Ganguli
2024	J	`jnl`	Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning. CoRR Daniel Kunin, Allan Raventós, Clémentine C. J. Dominé, Feng Chen, David A. Klindt, Andrew M. Saxe, Surya Ganguli
2024	A*	`conf`	Global Distortions from Local Rewards: Neural Coding Strategies in Path-Integrating Neural Systems. NeurIPS Francisco Acosta, Fatih Dinc, William Redman, Manu S. Madhav, David A. Klindt, Nina Miolane
2024	A*	`conf`	Measuring Per-Unit Interpretability at Scale Without Humans. NeurIPS Roland S. Zimmermann, David A. Klindt, Wieland Brendel
2024	J	`jnl`	Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations? CoRR Mark Ibrahim, David A. Klindt, Randall Balestriero
2023	J	`jnl`	Controlling Neural Network Smoothness for Neural Algorithmic Reasoning. Trans. Mach. Learn. Res. David A. Klindt
2023	J	`jnl`	Efficient coding of natural scenes improves neural system identification. PLoS Comput. Biol. Yongrong Qiu, David A. Klindt, Klaudia P. Szatko, Dominic Gonschorek, Larissa Höfling, Timm Schubert, Laura Busse, Matthias Bethge, Thomas Euler
2023	J	`jnl`	Identifying Interpretable Visual Features in Artificial and Biological Neural Systems. CoRR David A. Klindt, Sophia Sanborn, Francisco Acosta, Frédéric Poitevin, Nina Miolane
2023	A*	`conf`	Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles. ICLR Martin Bjerke, Lukas Schott, Kristopher T. Jensen, Claudia Battistin, David A. Klindt, Benjamin Adric Dunn
2022	—	`conf`	ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. TAG-ML 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
2022	J	`jnl`	ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results. CoRR 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
2022	—	`conf`	Topological ensemble detection with differentiable yoking. NeurReps David A. Klindt, Sigurd Gaukstad, Melvin Vaupel, Erik Hermansen, Benjamin A. Dunn
2022	J	`jnl`	Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles. CoRR Martin Bjerke, Lukas Schott, Kristopher T. Jensen, Claudia Battistin, David A. Klindt, Benjamin A. Dunn
2021	A*	`conf`	Removing Inter-Experimental Variability from Functional Data in Systems Neuroscience. NeurIPS Dominic Gonschorek, Larissa Höfling, Klaudia P. Szatko, Katrin Franke, Timm Schubert, Benjamin A. Dunn, Philipp Berens, David A. Klindt, Thomas Euler
2021	J	`jnl`	Score-Based Generative Classifiers. CoRR Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt
2021	A*	`conf`	Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding. ICLR David A. Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan M. Paiton
2020	A*	`conf`	System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina. NeurIPS Cornelius Schröder, David A. Klindt, Sarah Strauß, Katrin Franke, Matthias Bethge, Thomas Euler, Philipp Berens
2020	J	`jnl`	Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding. CoRR David A. Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan M. Paiton
2017	—	`conf`	Neural system identification for large populations separating "what" and "where". NIPS David A. Klindt, Alexander S. Ecker, Thomas Euler, Matthias Bethge
2017	J	`jnl`	Neural system identification for large populations separating "what" and "where". CoRR David A. Klindt, Alexander S. Ecker, Thomas Euler, Matthias Bethge