Asja Fischer

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 88

Top Venues

Publications

Mike Laszkiewicz, Imant Daunhawer, Julia E. Vogt, Asja Fischer, Johannes Lederer
Benchmarking the Fairness of Image Upsampling Methods. CoRR (2024)
Mike Laszkiewicz, Imant Daunhawer, Julia E. Vogt, Asja Fischer, Johannes Lederer
Benchmarking the Fairness of Image Upsampling Methods. FAccT (2024)
Sidak Pal Singh, Linara Adilova, Michael Kamp, Asja Fischer, Bernhard Schölkopf, Thomas Hofmann
Landscaping Linear Mode Connectivity. CoRR (2024)
Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Stefan Wrobel, Asja Fischer
Wasserstein dropout. Mach. Learn. 113 (5) (2024)
Jonas Ricker, Denis Lukovnikov, Asja Fischer
AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error. CoRR (2024)
Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke
Learning Sparse Codes with Entropy-Based ELBOs. AISTATS (2024)
Kira Maag, Asja Fischer
Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation. WACV (2024)
Jonas Ricker, Dennis Assenmacher, Thorsten Holz, Asja Fischer, Erwin Quiring
AI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Images. CoRR (2024)
Denis Lukovnikov, Asja Fischer
Layout-to-Image Generation with Localized Descriptions using ControlNet with Cross-Attention Control. CoRR (2024)
Kira Maag, Asja Fischer
Uncertainty-Based Detection of Adversarial Attacks in Semantic Segmentation. VISIGRAPP (2): VISAPP (2024)
Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi
Layer-wise linear mode connectivity. ICLR (2024)
Simon Damm, Mike Laszkiewicz, Johannes Lederer, Asja Fischer
AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2. CoRR (2024)
Laura Manduchi, 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 T. 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
On the Challenges and Opportunities in Generative AI. CoRR (2024)
Jonas Ricker, Simon Damm, Thorsten Holz, Asja Fischer
Towards the Detection of Diffusion Model Deepfakes. VISIGRAPP (4): VISAPP (2024)
Yulian Sun, Li Duan, Ricardo Mendes, Derui Zhu, Yue Xia, Yong Li, Asja Fischer
Exploiting Internal Randomness for Privacy in Vertical Federated Learning. IACR Cryptol. ePrint Arch. 2024 (2024)
Joel Frank, Franziska Herbert, Jonas Ricker, Lea Schönherr, Thorsten Eisenhofer, Asja Fischer, Markus Dürmuth, Thorsten Holz
A Representative Study on Human Detection of Artificially Generated Media Across Countries. CoRR (2023)
Kira Maag, Asja Fischer
Uncertainty-based Detection of Adversarial Attacks in Semantic Segmentation. CoRR (2023)
Linara Adilova, Bernhard C. Geiger, Asja Fischer
Information Plane Analysis for Dropout Neural Networks. CoRR (2023)
Linara Adilova, Asja Fischer, Martin Jaggi
Layerwise Linear Mode Connectivity. CoRR (2023)
Mike Laszkiewicz, Jonas Ricker, Johannes Lederer, Asja Fischer
Single-Model Attribution via Final-Layer Inversion. CoRR (2023)
Linara Adilova, Bernhard C. Geiger, Asja Fischer
Information Plane Analysis for Dropout Neural Networks. ICLR (2023)
Mike Laszkiewicz, Denis Lukovnikov, Johannes Lederer, Asja Fischer
Set-Membership Inference Attacks using Data Watermarking. CoRR (2023)
Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke
The ELBO of Variational Autoencoders Converges to a Sum of Entropies. AISTATS (2023)
Matías P. Pizarro B., Dorothea Kolossa, Asja Fischer
Leveraging characteristics of the output probability distribution for identifying adversarial audio examples. CoRR (2023)
Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke
Learning Sparse Codes with Entropy-Based ELBOs. CoRR (2023)
Kira Maag, Asja Fischer
Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation. CoRR (2023)
Mike Laszkiewicz, Johannes Lederer, Asja Fischer
Marginal Tail-Adaptive Normalizing Flows. ICML (2022)
Mike Laszkiewicz, Johannes Lederer, Asja Fischer
Marginal Tail-Adaptive Normalizing Flows. CoRR (2022)
Sina Däubener, Asja Fischer
How Sampling Impacts the Robustness of Stochastic Neural Networks. CoRR (2022)
Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Mikhail Galkin, Sahand Sharifzadeh, Asja Fischer, Volker Tresp, Jens Lehmann
Bringing Light Into the Dark: A Large-Scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Jonas Ricker, Simon Damm, Thorsten Holz, Asja Fischer
Towards the Detection of Diffusion Model Deepfakes. CoRR (2022)
Sina Däubener, Asja Fischer
How Sampling Impacts the Robustness of Stochastic Neural Networks. NeurIPS (2022)
Mike Laszkiewicz, Johannes Lederer, Asja Fischer
Copula-Based Normalizing Flows. CoRR (2021)
Denis Lukovnikov, Sina Däubener, Asja Fischer
Detecting Compositionally Out-of-Distribution Examples in Semantic Parsing. EMNLP (Findings) (2021)
Denis Lukovnikov, Asja Fischer
Insertion-based Tree Decoding. ACL/IJCNLP (Findings) (2021)
Arne P. Raulf, Sina Däubener, Ben Hack, Axel Mosig, Asja Fischer
SmoothLRP: Smoothing LRP by Averaging over Stochastic Input Variations. ESANN (2021)
Denis Lukovnikov, Asja Fischer
Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range Dependencies. ICML (2021)
Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel
A Novel Regression Loss for Non-Parametric Uncertainty Optimization. CoRR (2021)
Florian Linsner, Linara Adilova, Sina Däubener, Michael Kamp, Asja Fischer
Approaches to Uncertainty Quantification in Federated Deep Learning. PKDD/ECML Workshops (1) (2021)
Mike Laszkiewicz, Johannes Lederer, Asja Fischer
Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery. AISTATS (2021)
Diego Esteves, José Marcelino, Piyush Chawla, Asja Fischer, Jens Lehmann
HORUS-NER: A Multimodal Named Entity Recognition Framework for Noisy Data. IDA (2021)
Nilesh Chakraborty, Denis Lukovnikov, Gaurav Maheshwari, Priyansh Trivedi, Jens Lehmann, Asja Fischer
Introduction to neural network-based question answering over knowledge graphs. WIREs Data Mining Knowl. Discov. 11 (3) (2021)
Matias Pizarro, Dorothea Kolossa, Asja Fischer
Robustifying automatic speech recognition by extracting slowly varying features. CoRR (2021)
Kai Brügge, Asja Fischer, Christian Igel
On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions. AISTATS (2021)
Mike Laszkiewicz, Asja Fischer, Johannes Lederer
Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery. CoRR (2020)
Mohammad Asif Khan, Fabien Cardinaux, Stefan Uhlich, Marc Ferras, Asja Fischer
Unsupervised Cross-Domain Speech-to-Speech Conversion with Time-Frequency Consistency. CoRR (2020)
Sina Däubener, Lea Schönherr, Asja Fischer, Dorothea Kolossa
Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification. CoRR (2020)
Sina Däubener, Lea Schönherr, Asja Fischer, Dorothea Kolossa
Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification. INTERSPEECH (2020)
Joachim Sicking, Maram Akila, Tim Wirtz, Sebastian Houben, Asja Fischer
Characteristics of Monte Carlo Dropout in Wide Neural Networks. CoRR (2020)
Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, Thorsten Holz
Leveraging Frequency Analysis for Deep Fake Image Recognition. CoRR (2020)
Sina Däubener, Asja Fischer
Investigating maximum likelihood based training of infinite mixtures for uncertainty quantification. CoRR (2020)
Rostislav Nedelchev, Debanjan Chaudhuri, Jens Lehmann, Asja Fischer
End-to-End Entity Linking and Disambiguation leveraging Word and Knowledge Graph Embeddings. CoRR (2020)
Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Mikhail Galkin, Sahand Sharifzadeh, Asja Fischer, Volker Tresp, Jens Lehmann
Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework. CoRR (2020)
Oswin Krause, Asja Fischer, Christian Igel
Algorithms for estimating the partition function of restricted Boltzmann machines. Artif. Intell. 278 (2020)
Denis Lukovnikov, Asja Fischer, Jens Lehmann
Pretrained Transformers for Simple Question Answering over Knowledge Graphs. CoRR (2020)
Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, Thorsten Holz
Leveraging Frequency Analysis for Deep Fake Image Recognition. ICML (2020)
Kai Brügge, Asja Fischer, Christian Igel
On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions. CoRR (2020)
Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel
Second-Moment Loss: A Novel Regression Objective for Improved Uncertainties. CoRR (2020)
Oswin Krause, Asja Fischer, Christian Igel
Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract). IJCAI (2020)
Sven Koitka, Moon S. Kim, Ming Qu, Asja Fischer, Christoph M. Friedrich, Felix Nensa
Mimicking the radiologists' workflow: Estimating pediatric hand bone age with stacked deep neural networks. Medical Image Anal. 64 (2020)
Denis Lukovnikov, Jens Lehmann, Asja Fischer
Improving the Long-Range Performance of Gated Graph Neural Networks. CoRR (2020)
Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length. ICLR (Poster) (2019)
Denis Lukovnikov, Asja Fischer, Jens Lehmann
Pretrained Transformers for Simple Question Answering over Knowledge Graphs. ISWC (1) (2019)
Agustinus Kristiadi, Asja Fischer
Predictive Uncertainty Quantification with Compound Density Networks. CoRR (2019)
Gaurav Maheshwari, Priyansh Trivedi, Denis Lukovnikov, Nilesh Chakraborty, Asja Fischer, Jens Lehmann
Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs. ISWC (1) (2019)
Nilesh Chakraborty, Denis Lukovnikov, Gaurav Maheshwari, Priyansh Trivedi, Jens Lehmann, Asja Fischer
Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs. CoRR (2019)
Agustinus Kristiadi, Mohammad Asif Khan, Denis Lukovnikov, Jens Lehmann, Asja Fischer
Incorporating Literals into Knowledge Graph Embeddings. ISWC (1) (2019)
Debanjan Chaudhuri, Agustinus Kristiadi, Jens Lehmann, Asja Fischer
Improving Response Selection in Multi-turn Dialogue Systems. CoRR (2018)
Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
DNN's Sharpest Directions Along the SGD Trajectory. CoRR (2018)
Denis Lukovnikov, Nilesh Chakraborty, Jens Lehmann, Asja Fischer
Translating Natural Language to SQL using Pointer-Generator Networks and How Decoding Order Matters. CoRR (2018)
Agustinus Kristiadi, Mohammad Asif Khan, Denis Lukovnikov, Jens Lehmann, Asja Fischer
Incorporating Literals into Knowledge Graph Embeddings. CoRR (2018)
Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio. ICANN (3) (2018)
Gaurav Maheshwari, Priyansh Trivedi, Denis Lukovnikov, Nilesh Chakraborty, Asja Fischer, Jens Lehmann
Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs. CoRR (2018)
Henning Petzka, Asja Fischer, Denis Lukovnikov
On the regularization of Wasserstein GANs. ICLR (Poster) (2018)
Oswin Krause, Asja Fischer, Christian Igel
Population-Contrastive-Divergence: Does consistency help with RBM training? Pattern Recognit. Lett. 102 (2018)
Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
Finding Flatter Minima with SGD. ICLR (Workshop) (2018)
Debanjan Chaudhuri, Agustinus Kristiadi, Jens Lehmann, Asja Fischer
Improving Response Selection in Multi-Turn Dialogue Systems by Incorporating Domain Knowledge. CoNLL (2018)
Denis Lukovnikov, Asja Fischer, Jens Lehmann, Sören Auer
Neural Network-based Question Answering over Knowledge Graphs on Word and Character Level. WWW (2017)
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
A Closer Look at Memorization in Deep Networks. ICML (2017)
Yoshua Bengio, Thomas Mesnard, Asja Fischer, Saizheng Zhang, Yuhuai Wu
STDP-Compatible Approximation of Backpropagation in an Energy-Based Model. Neural Comput. 29 (3) (2017)
David Krueger, Nicolas Ballas, Stanislaw Jastrzebski, Devansh Arpit, Maxinder S. Kanwal, Tegan Maharaj, Emmanuel Bengio, Asja Fischer, Aaron C. Courville
Deep Nets Don't Learn via Memorization. ICLR (Workshop) (2017)
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
A Closer Look at Memorization in Deep Networks. CoRR (2017)
Björn Weghenkel, Asja Fischer, Laurenz Wiskott
Graph-based predictable feature analysis. Mach. Learn. 106 (9-10) (2017)
Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
Three Factors Influencing Minima in SGD. CoRR (2017)
Henning Petzka, Asja Fischer, Denis Lukovnikov
On the regularization of Wasserstein GANs. CoRR (2017)
Björn Weghenkel, Asja Fischer, Laurenz Wiskott
Graph-based Predictable Feature Analysis. CoRR (2016)
Jan Melchior, Asja Fischer, Laurenz Wiskott
How to Center Deep Boltzmann Machines. J. Mach. Learn. Res. 17 (2016)
Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio
Bidirectional Helmholtz Machines. ICML (2016)
Oswin Krause, Asja Fischer, Christian Igel
Population-Contrastive-Divergence: Does Consistency help with RBM training? CoRR (2015)
Dong-Hyun Lee, Saizheng Zhang, Asja Fischer, Yoshua Bengio
Difference Target Propagation. ECML/PKDD (1) (2015)
Yoshua Bengio, Thomas Mesnard, Asja Fischer, Saizheng Zhang, Yuhai Wu
An objective function for STDP. CoRR (2015)
Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio
Training opposing directed models using geometric mean matching. CoRR (2015)
Asja Fischer
Training Restricted Boltzmann Machines. Künstliche Intell. 29 (4) (2015)
Asja Fischer, Christian Igel
A bound for the convergence rate of parallel tempering for sampling restricted Boltzmann machines. Theor. Comput. Sci. 598 (2015)
Asja Fischer, Christian Igel
Training restricted Boltzmann machines: An introduction. Pattern Recognit. 47 (1) (2014)
Oswin Krause, Asja Fischer, Tobias Glasmachers, Christian Igel
Approximation properties of DBNs with binary hidden units and real-valued visible units. ICML (1) (2013)
Kai Brügge, Asja Fischer, Christian Igel
The flip-the-state transition operator for restricted Boltzmann machines. Mach. Learn. 93 (1) (2013)
Jan Melchior, Asja Fischer, Nan Wang, Laurenz Wiskott
How to Center Binary Restricted Boltzmann Machines. CoRR (2013)
Asja Fischer, Christian Igel
An Introduction to Restricted Boltzmann Machines. CIARP (2012)
Asja Fischer, Christian Igel
Training RBMs based on the signs of the CD approximation of the log-likelihood derivatives. ESANN (2011)

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Publication Activity (10 Years)

Top Topics

Top Venues

Asja Fischer