Konstantin-Klemens Lurz

Graduate Student

My interest lies in the topic of system identification, i.e. the finding of a mathematical model that maps the measurements of system inputs (visual stimuli) to system outputs (neuronal activity in the visual cortex of mice). The approach I chose for fitting these models is machine learning, more precisely deep convolutional neural networks (DCNNs). Identifying the underlying computations in a biological neural network using DCNNs can help the field in two ways: It can 1) provide insights about the functioning of biological neural networks for the neuroscience community and 2) it can identify useful inductive biases to be transferred to artificial neural networks for the machine learning community. My current project revolves around fitting such models that generalize between animals of the same species. Only if this condition is met, we can assume that the fitted model is not susceptible to subject-specific features and noise but captures general non-linear features that are characteristic for the visual cortex of mice as a whole.

Lab members are shown in this color.

2023

Suhas Shrinivasan, Konstantin-Klemens Lurz, Kelli Restivo, George Denfield, Andreas S. Tolias, Edgar Y. Walker¹, Fabian H. Sinz¹ Taking the neural sampling code very seriously: A data-driven approach for assessing generative models of the visual system NeurIPS , equal contribution: ¹ conference paper · normative_models ·
Konstantin F. Willeke, Paul G. Fahey, Mohammad Bashiri, Laura Hansel, Christoph Blessing, Konstantin-Klemens Lurz, Max F. Burg, Santiago A. Cadena, Zhiwei Ding, Kayla Ponder, Taliah Muhammad, Saumil S. Patel, Kaiwen Deng, Yuanfang Guan, Yiqin Zhu, Kaiwen Xiao, Xiao Han, Simone Azeglio, Ulisse Ferrari, Peter Neri, Olivier Marre, Adrian Hoffmann, Kirill Fedyanin, Kirill Vishniakov, Maxim Panov, Subash Prakash, Kishan Naik, Kantharaju Narayanappa, Alexander S. Ecker, Andreas S. Tolias, Fabian H. Sinz Retrospective on the SENSORIUM 2022 competition Proceedings of Machine Learning Research journal paper · system_identification · competition page PMLR pdf
Konstantin-Klemens Lurz¹, Mohammad Bashiri¹, Edgar Y. Walker, Fabian H. Sinz Bayesian Oracle for bounding information gain in neural encoding models ICLR 2023 (accepted) , equal contribution: ¹ conference paper · system identification · openreview code video

2022

Konstantin Lurz, Mohammad Bashiri, Fabian Sinz Bayesian Oracle for bounding information gain in neural encoding models Neurips 2022 Workshop InfoCog workshop paper · system identification ·
Konstantin F. Willeke, Paul G. Fahey, Mohammad Bashiri, Laura Pede, Max F. Burg, Christoph Blessing, Santiago A. Cadena, Zhiwei Ding, Konstantin-Klemens Lurz, Kayla Ponder, Taliah Muhammad, Saumil S. Patel, Alexander S. Ecker, Andreas S. Tolias, Fabian H. Sinz The Sensorium competition on predicting large-scale mouse primary visual cortex activity arXiv preprint · system identification · arXiv challenge data

2021

Mohammad Bashiri, Edgar Y. Walker, Konstantin-Klemens Lurz, Akshay Kumar Jagadish, Taliah Muhammad, Zhiwei Ding, Zhuokun Ding, Andreas S. Tolias, Fabian H. Sinz A flow-based latent state generative model of neural population responses to natural images NeurIPS (spotlight) conference paper · system identification · openreview twitter teaser-youtube talk-youtube github simulation demo biorXiv
Konstantin-Klemens Lurz, Mohammad Bashiri, Konstantin Friedrich Willeke, Akshay Kumar Jagadish, Eric Wang, Edgar Y Walker, Santiago Cadena, Taliah Muhammad, Eric Cobos, Andreas Tolias, Alexander Ecker, Fabian Sinz Generalization in data-driven models of primary visual cortex ICLR (spotlight) conference paper · system identification · openreview bioRxiv twitter data code youtube

2018

Konstantin-Klemens Lurz Natural Language Processing in Artificial Neuronal Networks: Sentence analysis in medical papers Lund University Library master thesis · Lund University Library