Fischer, Asja

40 publications

WACV 2025 AnomalyDINO: Boosting Patch-Based Few-Shot Anomaly Detection with DINOv2 Simon Damm, Mike Laszkiewicz, Johannes Lederer, Asja Fischer

ICLRW 2025 Are Semantic Watermarks for Diffusion Models Resilient to Layout Control? Denis Lukovnikov, Andreas Müller, Jonas Thietke, Erwin Quiring, Asja Fischer

CVPR 2025 Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models Andreas Müller, Denis Lukovnikov, Jonas Thietke, Asja Fischer, Erwin Quiring

UAI 2025 ELBO, Regularized Maximum Likelihood, and Their Common One-Sample Approximation for Training Stochastic Neural Networks Sina Däubener, Simon Damm, Asja Fischer

ECML-PKDD 2025 Enabling ControlNet to Follow Localized Descriptions Using Cross-Attention Control Denis Lukovnikov, Asja Fischer

TMLR 2025 On the Challenges and Opportunities in Generative AI Laura Manduchi, Clara Meister, Kushagra Pandey, Robert Bamler, Ryan Cotterell, Sina Däubener, Sophie Fellenz, Asja Fischer, Thomas Gärtner, Matthias Kirchler, Marius Kloft, Yingzhen Li, Christoph Lippert, Gerard de Melo, Eric Nalisnick, Björn Ommer, Rajesh Ranganath, Maja Rudolph, Karen Ullrich, Guy Van den Broeck, Julia E Vogt, Yixin Wang, Florian Wenzel, Frank Wood, Stephan Mandt, Vincent Fortuin

ICLRW 2025 Towards a Correct Usage of Cryptography in Semantic Watermarks for Diffusion Models Jonas Thietke, Andreas Müller, Denis Lukovnikov, Asja Fischer, Erwin Quiring

CVPR 2024 AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error Jonas Ricker, Denis Lukovnikov, Asja Fischer

ICMLW 2024 Landscaping Linear Mode Connectivity Sidak Pal Singh, Linara Adilova, Michael Kamp, Asja Fischer, Bernhard Schölkopf, Thomas Hofmann

ICLR 2024 Layer-Wise Linear Mode Connectivity Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi

AISTATS 2024 Learning Sparse Codes with Entropy-Based ELBOs Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke

ICML 2024 Single-Model Attribution of Generative Models Through Final-Layer Inversion Mike Laszkiewicz, Jonas Ricker, Johannes Lederer, Asja Fischer

WACV 2024 Uncertainty-Weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation Kira Maag, Asja Fischer

MLJ 2024 Wasserstein Dropout Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Stefan Wrobel, Asja Fischer

ICLR 2023 Information Plane Analysis for Dropout Neural Networks Linara Adilova, Bernhard C Geiger, Asja Fischer

AISTATS 2023 The ELBO of Variational Autoencoders Converges to a Sum of Entropies Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke

NeurIPS 2022 How Sampling Impacts the Robustness of Stochastic Neural Networks Sina Däubener, Asja Fischer

ECML-PKDD 2022 Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas

ECML-PKDD 2022 Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas

ECML-PKDD 2022 Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part III Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas

ECML-PKDD 2022 Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part IV Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas

ECML-PKDD 2022 Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part V Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas

ECML-PKDD 2022 Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part VI Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas

ICML 2022 Marginal Tail-Adaptive Normalizing Flows Mike Laszkiewicz, Johannes Lederer, Asja Fischer

AISTATS 2021 On the Convergence of the Metropolis Algorithm with Fixed-Order Updates for Multivariate Binary Probability Distributions Kai Brügge, Asja Fischer, Christian Igel

AISTATS 2021 Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery Mike Laszkiewicz, Asja Fischer, Johannes Lederer

ICMLW 2021 Copula-Based Normalizing Flows Mike Laszkiewicz, Johannes Lederer, Asja Fischer

ICML 2021 Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range Dependencies. Denis Lukovnikov, Asja Fischer

IJCAI 2020 Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract) Oswin Krause, Asja Fischer, Christian Igel

ICML 2020 Leveraging Frequency Analysis for Deep Fake Image Recognition Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, Thorsten Holz

ICLR 2019 On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length Stanisław Jastrzębski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos Storkey

ICLR 2018 On the Regularization of Wasserstein GANs Henning Petzka, Asja Fischer, Denis Lukovnikov

ICML 2017 A Closer Look at Memorization in Deep Networks Devansh Arpit, Stanisław Jastrzębski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, Simon Lacoste-Julien

ICLR 2017 Deep Nets Don't Learn via Memorization David Krueger, Nicolas Ballas, Stanislaw Jastrzebski, Devansh Arpit, Maxinder S. Kanwal, Tegan Maharaj, Emmanuel Bengio, Asja Fischer, Aaron C. Courville

MLJ 2017 Graph-Based Predictable Feature Analysis Björn Weghenkel, Asja Fischer, Laurenz Wiskott

ICML 2016 Bidirectional Helmholtz Machines Jorg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio

JMLR 2016 How to Center Deep Boltzmann Machines Jan Melchior, Asja Fischer, Laurenz Wiskott

ECML-PKDD 2015 Difference Target Propagation Dong-Hyun Lee, Saizheng Zhang, Asja Fischer, Yoshua Bengio

ICML 2013 Approximation Properties of DBNs with Binary Hidden Units and Real-Valued Visible Units Oswin Krause, Asja Fischer, Tobias Glasmachers, Christian Igel

MLJ 2013 The Flip-the-State Transition Operator for Restricted Boltzmann Machines Kai Brügge, Asja Fischer, Christian Igel