| 2026 | CHI | "That's another doom I haven't thought about": A User Study on AI Labels as a Safeguard Against Image-Based Misinformation. | Sandra Hltervennhoff, Jonas Ricker, Maike M. Raphael, Charlotte Schwedes, Rebecca Weil, Asja Fischer, Thorsten Holz, Lea Schnherr, Sascha Fahl |
| 2026 | ESANN | Revisiting Neural Activation Coverage for Uncertainty Estimation. | Benedikt Franke, Nils Frster, Frank Kster, Markus Lange, Arne P. Raulf, Asja Fischer |
| 2025 | ASIACRYPT | Solving Concealed ILWE and Its Application for Breaking Masked Dilithium. | Simon Damm, Asja Fischer, Alexander May, Soundes Marzougui, Leander Schwarz, Henning Seidler, Jean-Pierre Seifert, Jonas Thietke, Vincent Quentin Ulitzsch |
| 2025 | CVPR | Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models. | Andreas Mller, Denis Lukovnikov, Jonas Thietke, Asja Fischer, Erwin Quiring |
| 2025 | EMNLP | Can LLMs Explain Themselves Counterfactually? | Zahra Dehghanighobadi, Asja Fischer, Muhammad Bilal Zafar |
| 2025 | WACV | AnomalyDINO: Boosting Patch-based Few-Shot Anomaly Detection with DINOv2. | Simon Damm, Mike Laszkiewicz, Johannes Lederer, Asja Fischer |
| 2025 | UAI | ELBO, regularized maximum likelihood, and their common one-sample approximation for training stochastic neural networks. | Sina Dubener, Simon Damm, Asja Fischer |
| 2024 | AISTATS | Learning Sparse Codes with Entropy-Based ELBOs. | Dmytro Velychko, Simon Damm, Asja Fischer, Jrg Lcke |
| 2024 | CVPR | AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error. | Jonas Ricker, Denis Lukovnikov, Asja Fischer |
| 2024 | ESORICS | Exploiting Internal Randomness for Privacy in Vertical Federated Learning. | Yulian Sun, Li Duan, Ricardo Mendes, Derui Zhu, Yue Xia, Yong Li, Asja Fischer |
| 2024 | ICLR | Layer-wise linear mode connectivity. | Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi |
| 2024 | ICML | Single-Model Attribution of Generative Models Through Final-Layer Inversion. | Mike Laszkiewicz, Jonas Ricker, Johannes Lederer, Asja Fischer |
| 2024 | RAID | AI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Images. | Jonas Ricker, Dennis Assenmacher, Thorsten Holz, Asja Fischer, Erwin Quiring |
| 2024 | WACV | Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation. | Kira Maag, Asja Fischer |
| 2024 | UAI | DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution. | Matas P. Pizarro B., Dorothea Kolossa, Asja Fischer |
| 2024 | SP | A Representative Study on Human Detection of Artificially Generated Media Across Countries. | Joel Frank, Franziska Herbert, Jonas Ricker, Lea Schnherr, Thorsten Eisenhofer, Asja Fischer, Markus Drmuth, Thorsten Holz |
| 2024 | VISIGRAPP | Uncertainty-Based Detection of Adversarial Attacks in Semantic Segmentation. | Kira Maag, Asja Fischer |
| 2024 | VISIGRAPP | Towards the Detection of Diffusion Model Deepfakes. | Jonas Ricker, Simon Damm, Thorsten Holz, Asja Fischer |
| 2023 | AISTATS | The ELBO of Variational Autoencoders Converges to a Sum of Entropies. | Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jrg Lcke |
| 2023 | ICLR | Information Plane Analysis for Dropout Neural Networks. | Linara Adilova, Bernhard C. Geiger, Asja Fischer |
| 2022 | ICML | Marginal Tail-Adaptive Normalizing Flows. | Mike Laszkiewicz, Johannes Lederer, Asja Fischer |
| 2021 | ACL | Insertion-based Tree Decoding. | Denis Lukovnikov, Asja Fischer |
| 2021 | AISTATS | On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions. | Kai Brgge, Asja Fischer, Christian Igel |
| 2021 | AISTATS | Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery. | Mike Laszkiewicz, Asja Fischer, Johannes Lederer |
| 2021 | EMNLP | Detecting Compositionally Out-of-Distribution Examples in Semantic Parsing. | Denis Lukovnikov, Sina Dubener, Asja Fischer |
| 2021 | ESANN | SmoothLRP: Smoothing LRP by Averaging over Stochastic Input Variations. | Arne P. Raulf, Sina Dubener, Ben Hack, Axel Mosig, Asja Fischer |
| 2021 | ICML | Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range Dependencies. | Denis Lukovnikov, Asja Fischer |
| 2021 | IDA | HORUS-NER: A Multimodal Named Entity Recognition Framework for Noisy Data. | Diego Esteves, Jos Marcelino, Piyush Chawla, Asja Fischer, Jens Lehmann |
| 2020 | ICML | Leveraging Frequency Analysis for Deep Fake Image Recognition. | Joel Frank, Thorsten Eisenhofer, Lea Schnherr, Asja Fischer, Dorothea Kolossa, Thorsten Holz |
| 2020 | IJCAI | Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract). | Oswin Krause, Asja Fischer, Christian Igel |
| 2020 | Interspeech | Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification. | Sina Dubener, Lea Schnherr, Asja Fischer, Dorothea Kolossa |
| 2019 | ICLR | On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length. | Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey |
| 2018 | CoNLL | Improving Response Selection in Multi-Turn Dialogue Systems by Incorporating Domain Knowledge. | Debanjan Chaudhuri, Agustinus Kristiadi, Jens Lehmann, Asja Fischer |
| 2018 | ICANN | Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio. | Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey |
| 2018 | ICLR | Finding Flatter Minima with SGD. | Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey |
| 2018 | ICLR | On the regularization of Wasserstein GANs. | Henning Petzka, Asja Fischer, Denis Lukovnikov |
| 2017 | ICLR | 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 |
| 2017 | ICML | A Closer Look at Memorization in Deep Networks. | Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S. Kanwal, Tegan Maharaj, Asja Fischer, Aaron C. Courville, Yoshua Bengio, Simon Lacoste-Julien |
| 2017 | WWW | Neural Network-based Question Answering over Knowledge Graphs on Word and Character Level. | Denis Lukovnikov, Asja Fischer, Jens Lehmann, Sren Auer |
| 2016 | ICML | Bidirectional Helmholtz Machines. | Jrg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio |
| 2013 | ICML | Approximation properties of DBNs with binary hidden units and real-valued visible units. | Oswin Krause, Asja Fischer, Tobias Glasmachers, Christian Igel |
| 2012 | CIARP | An Introduction to Restricted Boltzmann Machines. | Asja Fischer, Christian Igel |
| 2011 | ESANN | Training RBMs based on the signs of the CD approximation of the log-likelihood derivatives. | Asja Fischer, Christian Igel |
| 2010 | ICANN | Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines. | Asja Fischer, Christian Igel |