Katja Seeliger

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All published works

Action	Title	Year	Authors
+ PDF Chat	Neural encoding with affine feature response transforms	2025	Lynn Le Nils Kimman Thirza Dado Katja Seeliger Paolo Papale Antonio Lozano Pieter R. Roelfsema Marcel van Gerven Yağmur Güçlütürk Umut Güçlü
+ PDF Chat	Inverse receptive field attention for naturalistic image reconstruction from the brain	2025	Lynn Le Thirza Dado Katja Seeliger Paolo Papale Antonio Lozano Pieter R. Roelfsema Yağmur Güçlütürk Marcel van Gerven Umut Güçlü
+ PDF Chat	The neuroconnectionist research programme	2023	Adrien Doerig Rowan P. Sommers Katja Seeliger Blake A. Richards Jenann Ismael Grace W. Lindsay Konrad P. Körding Talia Konkle Marcel van Gerven Nikolaus Kriegeskorte
+	Deep neural networks are not a single hypothesis but a language for expressing computational hypotheses	2023	Tal Golan JohnMark Taylor Heiko H. Schütt Benjamin Peters Rowan Paolo Sommers Katja Seeliger Adrien Doerig Paul Linton Talia Konkle Marcel van Gerven
+ PDF Chat	Deep neural networks are not a single hypothesis but a language for expressing computational hypotheses	2023	Tal Golan JohnMark Taylor Heiko H. Schütt Benjamin Peters Rowan P. Sommers Katja Seeliger Adrien Doerig Paul Linton Talia Konkle Marcel van Gerven
+	The neuroconnectionist research programme	2022	Adrien Doerig Rowan P. Sommers Katja Seeliger Blake A. Richards Jenann Ismael Grace Lindsay Konrad P. Körding Talia Konkle Marcel van Gerven Nikolaus Kriegeskorte
+	From photos to sketches - how humans and deep neural networks process objects across different levels of visual abstraction	2021	Johannes Singer Katja Seeliger Tim C. Kietzmann Martin N. Hebart
+	Generalization of an Upper Bound on the Number of Nodes Needed to Achieve Linear Separability	2018	Marjolein Troost Katja Seeliger Marcel van Gerven
+	Deep adversarial neural decoding	2017	Yağmur Güçlütürk Umut Güçlü Katja Seeliger Sander Bosch Rob van Lier Marcel van Gerven
+	Deep adversarial neural decoding	2017	Yağmur Güçlütürk Umut Güçlü Katja Seeliger Sander Bosch Rob van Lier Marcel van Gerven
+	Deep adversarial neural decoding	2017	Yağmur Güçlütürk Umut Güçlü Katja Seeliger Sander Bosch Rob van Lier Marcel van Gerven

Common Coauthors

Coauthor	Papers Together
Marcel van Gerven	10
Tim C. Kietzmann	5
Yağmur Güçlütürk	5
Umut Güçlü	5
Adrien Doerig	4
Nikolaus Kriegeskorte	4
Konrad P. Körding	4
Talia Konkle	4
Sander Bosch	3
Rowan P. Sommers	3
Rob van Lier	3
Antonio Lozano	2
Paul Linton	2
Tal Golan	2
Blake Richards	2
Blake A. Richards	2
Pieter R. Roelfsema	2
Thirza Dado	2
Paolo Papale	2
JohnMark Taylor	2
Lynn Le	2
Grace W. Lindsay	2
Benjamin Peters	2
Jenann Ismael	2
Heiko H. Schütt	2
Nils Kimman	1
Grace W. Lindsay	1
Marjolein Troost	1
Rowan Paolo Sommers	1
Martin N. Hebart	1
Johannes Singer	1
Grace Lindsay	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream	2015	Umut Güçlü Marcel van Gerven	5
+ PDF Chat	Convolutional Neural Networks as a Model of the Visual System: Past, Present, and Future	2020	Grace W. Lindsay	3
+ PDF Chat	Controversial stimuli: Pitting neural networks against each other as models of human cognition	2020	Tal Golan Prashant C. Raju Nikolaus Kriegeskorte	3
+ PDF Chat	Permuted AdaIN: Reducing the Bias Towards Global Statistics in Image Classification	2021	Oren Nuriel Sagie Benaim Lior Wolf	2
+ PDF Chat	Capturing the objects of vision with neural networks	2021	Benjamin Peters Nikolaus Kriegeskorte	2
+ PDF Chat	Deep problems with neural network models of human vision	2022	Jeffrey S. Bowers Gaurav Malhotra Marin Dujmović Milton L. Montero Christian Tsvetkov Valerio Biscione Guillermo Puebla Federico Adolfi John E. Hummel Rachel F. Heaton	2
+ PDF Chat	Recurrence is required to capture the representational dynamics of the human visual system	2019	Tim C. Kietzmann Courtney J. Spoerer Lynn K. A. Sörensen Radoslaw M. Cichy Olaf Hauk Nikolaus Kriegeskorte	2
+ PDF Chat	Modeling the Dynamics of Human Brain Activity with Recurrent Neural Networks	2017	Umut Güçlü Marcel van Gerven	2
+	ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness	2018	Robert Geirhos Patricia Rubisch Claudio Michaelis Matthias Bethge Felix A. Wichmann Wieland Brendel	2
+	The Origins and Prevalence of Texture Bias in Convolutional Neural Networks	2019	Katherine L. Hermann Ting Chen Simon Kornblith	2
+	Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing	1995	Yoav Benjamini Yosef Hochberg	1
+ PDF Chat	Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision	2017	Haiguang Wen Junxing Shi Yizhen Zhang Kun‐Han Lu Jiayue Cao Zhongming Liu	1
+	Towards Deep Symbolic Reinforcement Learning	2016	Marta Garnelo Kai Arulkumaran Murray Shanahan	1
+	PsyPhy: A Psychophysics Driven Evaluation Framework for Visual Recognition	2018	Brandon RichardWebster Samuel Anthony Walter J. Scheirer	1
+ PDF Chat	Deep Neural Networks as a Computational Model for Human Shape Sensitivity	2016	Jonas Kubilius Stefania Bracci Hans Op de Beeck	1
+	Note on the sampling error of the difference between correlated proportions or percentages	1947	Quinn McNemar	1
+ PDF Chat	Deep neural networks are easily fooled: High confidence predictions for unrecognizable images	2015	Anh‐Tu Nguyen Jason Yosinski Jeff Clune	1
+ PDF Chat	Generating Visual Explanations	2016	Lisa Anne Hendricks Zeynep Akata Marcus Rohrbach Jeff Donahue Bernt Schiele Trevor Darrell	1
+	Linking Connectivity, Dynamics, and Computations in Low-Rank Recurrent Neural Networks	2018	Francesca Mastrogiuseppe Srdjan Ostojic	1
+ PDF Chat	Evaluating (and Improving) the Correspondence Between Deep Neural Networks and Human Representations	2018	Joshua C. Peterson Joshua T. Abbott Thomas L. Griffiths	1
+	A rotation-equivariant convolutional neural network model of primary visual cortex	2018	Alexander S. Ecker Fabian H. Sinz Emmanouil Froudarakis Paul G. Fahey Santiago A. Cadena Edgar Y. Walker Erick Cobos Jacob Reimer Andreas S. Tolias Matthias Bethge	1
+ PDF Chat	A mathematical theory of semantic development in deep neural networks	2019	Andrew Saxe James L. McClelland Surya Ganguli	1
+	Towards a Definition of Disentangled Representations	2018	Irina Higgins David Amos David Pfau Sébastien Racanière Löıc Matthey Danilo Jimenez Rezende Alexander Lerchner	1
+	Proceedings of the 25th international conference on Machine learning	2008	William W. Cohen Andrew McCallum Sam T. Roweis	1
+	Representation Similarity Analysis for Efficient Task taxonomy & Transfer Learning	2019	Kshitij Dwivedi Gemma Roig	1
+	Learning Robust Global Representations by Penalizing Local Predictive Power	2019	Haohan Wang Songwei Ge Eric P. Xing Zachary C. Lipton	1
+	Certified Adversarial Robustness via Randomized Smoothing	2019	Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter	1
+ PDF Chat	Toward an Integration of Deep Learning and Neuroscience	2016	Adam Marblestone Greg Wayne Konrad P. Körding	1
+	Generalisation in humans and deep neural networks	2018	Robert Geirhos Carlos R. Medina Temme Jonas Rauber Heiko H. Schütt Matthias Bethge Felix A. Wichmann	1
+	Very Deep Convolutional Networks for Large-Scale Image Recognition	2014	Karen Simonyan Andrew Zisserman	1
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	1
+ PDF Chat	Deep learning in neural networks: An overview	2014	Jürgen Schmidhuber	1
+ PDF Chat	Equivalence Tests	2017	Daniël Lakens	1
+	Crowding reveals fundamental differences in local vs. global processing in humans and machines	2020	Adrien Doerig Alban Bornet Oh-Hyeon Choung Michael H. Herzog	1
+	Sharing deep generative representation for perceived image reconstruction from human brain activity	2017	Changde Du Changying Du Huiguang He	1
+	Exact solutions to the nonlinear dynamics of learning in deep linear neural networks	2013	Andrew Saxe James L. McClelland Surya Ganguli	1
+	Towards Deep Learning Models Resistant to Adversarial Attacks.	2018	Aleksander Mądry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu	1
+	Going in circles is the way forward: the role of recurrence in visual inference	2020	Ruben S. van Bergen Nikolaus Kriegeskorte	1
+	A neural network walks into a lab: towards using deep nets as models for human behavior	2020	Wei Ji Benjamin Peters	1
+ PDF Chat	Artificial Neural Networks for Neuroscientists: A Primer	2020	Guangyu Robert Yang Xiao‐Jing Wang	1
+	Generic decoding of seen and imagined objects using hierarchical visual features	2017	Tomoyasu Horikawa Yukiyasu Kamitani	1
+	Deep Reinforcement Learning and Its Neuroscientific Implications	2020	Matthew Botvinick Jane X. Wang Will Dabney Kevin J Miller Zeb Kurth‐Nelson	1
+ PDF Chat	SAYCam: A Large, Longitudinal Audiovisual Dataset Recorded From the Infant’s Perspective	2021	Jessica Sullivan Michelle Mei Andrew Perfors Erica H. Wojcik Michael C. Frank	1
+	On the surprising similarities between supervised and self-supervised models	2020	Robert Geirhos Kantharaju Narayanappa Benjamin Mitzkus Matthias Bethge Felix A. Wichmann Wieland Brendel	1
+	An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale	2020	Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai Thomas Unterthiner Mostafa Dehghani Matthias Minderer Georg Heigold Sylvain Gelly	1
+	Opening the Black Box of Deep Neural Networks via Information	2017	Ravid Shwartz-Ziv Naftali Tishby	1
+ PDF Chat	Interpretable Explanations of Black Boxes by Meaningful Perturbation	2017	Ruth Fong Andrea Vedaldi	1
+ PDF Chat	SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks	2018	Friedemann Zenke Surya Ganguli	1
+ PDF Chat	Humans can decipher adversarial images	2019	Zhenglong Zhou Chaz Firestone	1
+	Analyzing biological and artificial neural networks: challenges with opportunities for synergy?	2019	David G. T. Barrett Ari S. Morcos Jakob H. Macke	1