Asja Fischer - RankMe

140 papers A* 16A 10B 4C 1Journal 83Unranked 20

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	"That's another doom I haven't thought about": A User Study on AI Labels as a Safeguard Against Image-Based Misinformation. CHI Sandra Höltervennhoff, Jonas Ricker, Maike M. Raphael, Charlotte Schwedes, Rebecca Weil, Asja Fischer, Thorsten Holz, Lea Schönherr, Sascha Fahl
2026	J	`jnl`	Comparative study on noise-augmented training and its effect on adversarial robustness in ASR systems. Comput. Speech Lang. Karla Pizzi, Matias Pizarro, Asja Fischer
2026	J	`jnl`	Precision-Varying Prediction (PVP): Robustifying ASR systems against adversarial attacks. CoRR Matías P. Pizarro B., Raghavan Narasimhan, Asja Fischer
2026	J	`jnl`	SAMSEM - A Generic and Scalable Approach for IC Metal Line Segmentation. CoRR Christian Gehrmann, Jonas Ricker, Simon Damm, Deruo Cheng, Julian Speith, Yiqiong Shi, Asja Fischer, Christof Paar
2025	A	`conf`	AnomalyDINO: Boosting Patch-based Few-Shot Anomaly Detection with DINOv2. WACV Simon Damm, Mike Laszkiewicz, Johannes Lederer, Asja Fischer
2025	A*	`conf`	Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models. CVPR Andreas Müller, Denis Lukovnikov, Jonas Thietke, Asja Fischer, Erwin Quiring
2025	A*	`conf`	Can LLMs Explain Themselves Counterfactually? EMNLP Zahra Dehghanighobadi, Asja Fischer, Muhammad Bilal Zafar
2025	J	`jnl`	Can LLMs Explain Themselves Counterfactually? CoRR Zahra Dehghanighobadi, Asja Fischer, Muhammad Bilal Zafar
2025	A	`conf`	ELBO, regularized maximum likelihood, and their common one-sample approximation for training stochastic neural networks. UAI Sina Däubener, Simon Damm, Asja Fischer
2025	—	`conf`	Enabling ControlNet to follow Localized Descriptions Using Cross-Attention Control. ECML/PKDD (2) Denis Lukovnikov, Asja Fischer
2025	J	`jnl`	Generative Models with ELBOs Converging to Entropy Sums. CoRR Jan Warnken, Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke
2025	J	`jnl`	On the Challenges and Opportunities in Generative AI. Trans. Mach. Learn. Res. 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 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
2025	J	`jnl`	PRADA: Probability-Ratio-Based Attribution and Detection of Autoregressive-Generated Images. CoRR Simon Damm, Jonas Ricker, Henning Petzka, Asja Fischer
2025	J	`jnl`	RAID: A Dataset for Testing the Adversarial Robustness of AI-Generated Image Detectors. CoRR Hicham Eddoubi, Jonas Ricker, Federico Cocchi, Lorenzo Baraldi, Angelo Sotgiu, Maura Pintor, Marcella Cornia, Lorenzo Baraldi, Asja Fischer, Rita Cucchiara, Battista Biggio
2025	J	`jnl`	Security Benefits and Side Effects of Labeling AI-Generated Images. CoRR Sandra Höltervennhoff, Jonas Ricker, Maike M. Raphael, Charlotte Schwedes, Rebecca Weil, Asja Fischer, Thorsten Holz, Lea Schönherr, Sascha Fahl
2025	—	`conf`	Solving Concealed ILWE and Its Application for Breaking Masked Dilithium. ASIACRYPT (2) Simon Damm, Asja Fischer, Alexander May, Soundes Marzougui, Leander Schwarz, Henning Seidler, Jean-Pierre Seifert, Jonas Thietke, Vincent Quentin Ulitzsch
2025	J	`jnl`	Solving Concealed ILWE and its Application for Breaking Masked Dilithium. IACR Cryptol. ePrint Arch. Simon Damm, Asja Fischer, Alexander May, Soundes Marzougui, Leander Schwarz, Henning Seidler, Jean-Pierre Seifert, Jonas Thietke, Vincent Quentin Ulitzsch
2025	J	`jnl`	Towards A Correct Usage of Cryptography in Semantic Watermarks for Diffusion Models. CoRR Jonas Thietke, Andreas Müller, Denis Lukovnikov, Asja Fischer, Erwin Quiring
2025	J	`jnl`	Towards Robust Red-Green Watermarking for Autoregressive Image Generators. CoRR Denis Lukovnikov, Andreas Müller, Erwin Quiring, Asja Fischer
2025	J	`jnl`	Towards an Optimal Control Perspective of ResNet Training. CoRR Jens Püttschneider, Simon Heilig, Asja Fischer, Timm Faulwasser
2024	A*	`conf`	A Representative Study on Human Detection of Artificially Generated Media Across Countries. SP Joel Frank, Franziska Herbert, Jonas Ricker, Lea Schönherr, Thorsten Eisenhofer, Asja Fischer, Markus Dürmuth, Thorsten Holz
2024	A*	`conf`	AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error. CVPR Jonas Ricker, Denis Lukovnikov, Asja Fischer
2024	J	`jnl`	AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error. CoRR Jonas Ricker, Denis Lukovnikov, Asja Fischer
2024	A	`conf`	AI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Images. RAID Jonas Ricker, Dennis Assenmacher, Thorsten Holz, Asja Fischer, Erwin Quiring
2024	J	`jnl`	AI-Generated Faces in the Real World: A Large-Scale Case Study of Twitter Profile Images. CoRR Jonas Ricker, Dennis Assenmacher, Thorsten Holz, Asja Fischer, Erwin Quiring
2024	J	`jnl`	AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2. CoRR Simon Damm, Mike Laszkiewicz, Johannes Lederer, Asja Fischer
2024	—	`conf`	Benchmarking the Fairness of Image Upsampling Methods. FAccT Mike Laszkiewicz, Imant Daunhawer, Julia E. Vogt, Asja Fischer, Johannes Lederer
2024	J	`jnl`	Benchmarking the Fairness of Image Upsampling Methods. CoRR Mike Laszkiewicz, Imant Daunhawer, Julia E. Vogt, Asja Fischer, Johannes Lederer
2024	J	`jnl`	Black-Box Forgery Attacks on Semantic Watermarks for Diffusion Models. CoRR Andreas Müller, Denis Lukovnikov, Jonas Thietke, Asja Fischer, Erwin Quiring
2024	J	`jnl`	Detecting Adversarial Attacks in Semantic Segmentation via Uncertainty Estimation: A Deep Analysis. CoRR Kira Maag, Roman Resner, Asja Fischer
2024	A	`conf`	DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution. UAI Matías P. Pizarro B., Dorothea Kolossa, Asja Fischer
2024	—	`conf`	Exploiting Internal Randomness for Privacy in Vertical Federated Learning. ESORICS (2) Yulian Sun, Li Duan, Ricardo Mendes, Derui Zhu, Yue Xia, Yong Li, Asja Fischer
2024	J	`jnl`	Exploiting Internal Randomness for Privacy in Vertical Federated Learning. IACR Cryptol. ePrint Arch. Yulian Sun, Li Duan, Ricardo Mendes, Derui Zhu, Yue Xia, Yong Li, Asja Fischer
2024	J	`jnl`	Fake It Until You Break It: On the Adversarial Robustness of AI-generated Image Detectors. CoRR Sina Mavali, Jonas Ricker, David Pape, Yash Sharma, Asja Fischer, Lea Schönherr
2024	J	`jnl`	Integrating uncertainty quantification into randomized smoothing based robustness guarantees. CoRR Sina Däubener, Kira Maag, David Krueger, Asja Fischer
2024	J	`jnl`	Landscaping Linear Mode Connectivity. CoRR Sidak Pal Singh, Linara Adilova, Michael Kamp, Asja Fischer, Bernhard Schölkopf, Thomas Hofmann
2024	A*	`conf`	Layer-wise linear mode connectivity. ICLR Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi
2024	J	`jnl`	Layout-to-Image Generation with Localized Descriptions using ControlNet with Cross-Attention Control. CoRR Denis Lukovnikov, Asja Fischer
2024	A	`conf`	Learning Sparse Codes with Entropy-Based ELBOs. AISTATS Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke
2024	J	`jnl`	On the Challenges and Opportunities in Generative AI. CoRR 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
2024	J	`jnl`	Reassessing Noise Augmentation Methods in the Context of Adversarial Speech. CoRR Karla Pizzi, Matías P. Pizarro B., Asja Fischer
2024	J	`jnl`	Single-Model Attribution for Spoofed Speech via Vocoder Fingerprints in an Open-World Setting. CoRR Matias Pizarro, Mike Laszkiewicz, Dorothea Kolossa, Asja Fischer
2024	A*	`conf`	Single-Model Attribution of Generative Models Through Final-Layer Inversion. ICML Mike Laszkiewicz, Jonas Ricker, Johannes Lederer, Asja Fischer
2024	—	`conf`	Towards the Detection of Diffusion Model Deepfakes. VISIGRAPP (4): VISAPP Jonas Ricker, Simon Damm, Thorsten Holz, Asja Fischer
2024	—	`conf`	Uncertainty-Based Detection of Adversarial Attacks in Semantic Segmentation. VISIGRAPP (2): VISAPP Kira Maag, Asja Fischer
2024	A	`conf`	Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation. WACV Kira Maag, Asja Fischer
2024	J	`jnl`	Wasserstein dropout. Mach. Learn. Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Stefan Wrobel, Asja Fischer
2023	J	`jnl`	A Representative Study on Human Detection of Artificially Generated Media Across Countries. CoRR Joel Frank, Franziska Herbert, Jonas Ricker, Lea Schönherr, Thorsten Eisenhofer, Asja Fischer, Markus Dürmuth, Thorsten Holz
2023	A*	`conf`	Information Plane Analysis for Dropout Neural Networks. ICLR Linara Adilova, Bernhard C. Geiger, Asja Fischer
2023	J	`jnl`	Information Plane Analysis for Dropout Neural Networks. CoRR Linara Adilova, Bernhard C. Geiger, Asja Fischer
2023	J	`jnl`	Layerwise Linear Mode Connectivity. CoRR Linara Adilova, Asja Fischer, Martin Jaggi
2023	J	`jnl`	Learning Sparse Codes with Entropy-Based ELBOs. CoRR Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke
2023	J	`jnl`	Leveraging characteristics of the output probability distribution for identifying adversarial audio examples. CoRR Matías P. Pizarro B., Dorothea Kolossa, Asja Fischer
2023	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part I ECML/PKDD (1) Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas
2023	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part II ECML/PKDD (2) Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas
2023	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part III ECML/PKDD (3) Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas
2023	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part IV ECML/PKDD (4) Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas
2023	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part V ECML/PKDD (5) Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas
2023	—	`ed.`	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2022, Grenoble, France, September 19-23, 2022, Proceedings, Part VI ECML/PKDD (6) Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas
2023	J	`jnl`	Set-Membership Inference Attacks using Data Watermarking. CoRR Mike Laszkiewicz, Denis Lukovnikov, Johannes Lederer, Asja Fischer
2023	J	`jnl`	Single-Model Attribution via Final-Layer Inversion. CoRR Mike Laszkiewicz, Jonas Ricker, Johannes Lederer, Asja Fischer
2023	A	`conf`	The ELBO of Variational Autoencoders Converges to a Sum of Entropies. AISTATS Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke
2023	J	`jnl`	Uncertainty-based Detection of Adversarial Attacks in Semantic Segmentation. CoRR Kira Maag, Asja Fischer
2023	J	`jnl`	Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation. CoRR Kira Maag, Asja Fischer
2022	J	`jnl`	Bringing Light Into the Dark: A Large-Scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework. IEEE Trans. Pattern Anal. Mach. Intell. Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Mikhail Galkin, Sahand Sharifzadeh, Asja Fischer, Volker Tresp, Jens Lehmann
2022	A*	`conf`	How Sampling Impacts the Robustness of Stochastic Neural Networks. NeurIPS Sina Däubener, Asja Fischer
2022	J	`jnl`	How Sampling Impacts the Robustness of Stochastic Neural Networks. CoRR Sina Däubener, Asja Fischer
2022	A*	`conf`	Marginal Tail-Adaptive Normalizing Flows. ICML Mike Laszkiewicz, Johannes Lederer, Asja Fischer
2022	J	`jnl`	Marginal Tail-Adaptive Normalizing Flows. CoRR Mike Laszkiewicz, Johannes Lederer, Asja Fischer
2022	J	`jnl`	Towards the Detection of Diffusion Model Deepfakes. CoRR Jonas Ricker, Simon Damm, Thorsten Holz, Asja Fischer
2021	J	`jnl`	A Novel Regression Loss for Non-Parametric Uncertainty Optimization. CoRR Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel
2021	—	`conf`	Approaches to Uncertainty Quantification in Federated Deep Learning. PKDD/ECML Workshops (1) Florian Linsner, Linara Adilova, Sina Däubener, Michael Kamp, Asja Fischer
2021	J	`jnl`	Copula-Based Normalizing Flows. CoRR Mike Laszkiewicz, Johannes Lederer, Asja Fischer
2021	—	`conf`	Detecting Compositionally Out-of-Distribution Examples in Semantic Parsing. EMNLP (Findings) Denis Lukovnikov, Sina Däubener, Asja Fischer
2021	B	`conf`	HORUS-NER: A Multimodal Named Entity Recognition Framework for Noisy Data. IDA Diego Esteves, José Marcelino, Piyush Chawla, Asja Fischer, Jens Lehmann
2021	A*	`conf`	Improving Breadth-Wise Backpropagation in Graph Neural Networks Helps Learning Long-Range Dependencies. ICML Denis Lukovnikov, Asja Fischer
2021	—	`conf`	Insertion-based Tree Decoding. ACL/IJCNLP (Findings) Denis Lukovnikov, Asja Fischer
2021	J	`jnl`	Introduction to neural network-based question answering over knowledge graphs. WIREs Data Mining Knowl. Discov. Nilesh Chakraborty, Denis Lukovnikov, Gaurav Maheshwari, Priyansh Trivedi, Jens Lehmann, Asja Fischer
2021	A	`conf`	On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions. AISTATS Kai Brügge, Asja Fischer, Christian Igel
2021	J	`jnl`	Robustifying automatic speech recognition by extracting slowly varying features. CoRR Matias Pizarro, Dorothea Kolossa, Asja Fischer
2021	B	`conf`	SmoothLRP: Smoothing LRP by Averaging over Stochastic Input Variations. ESANN Arne P. Raulf, Sina Däubener, Ben Hack, Axel Mosig, Asja Fischer
2021	A	`conf`	Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery. AISTATS Mike Laszkiewicz, Asja Fischer, Johannes Lederer
2020	A*	`conf`	Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract). IJCAI Oswin Krause, Asja Fischer, Christian Igel
2020	J	`jnl`	Algorithms for estimating the partition function of restricted Boltzmann machines. Artif. Intell. Oswin Krause, Asja Fischer, Christian Igel
2020	J	`jnl`	Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework. CoRR Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Mikhail Galkin, Sahand Sharifzadeh, Asja Fischer, Volker Tresp, Jens Lehmann
2020	J	`jnl`	Characteristics of Monte Carlo Dropout in Wide Neural Networks. CoRR Joachim Sicking, Maram Akila, Tim Wirtz, Sebastian Houben, Asja Fischer
2020	A	`conf`	Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification. INTERSPEECH Sina Däubener, Lea Schönherr, Asja Fischer, Dorothea Kolossa
2020	J	`jnl`	Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification. CoRR Sina Däubener, Lea Schönherr, Asja Fischer, Dorothea Kolossa
2020	J	`jnl`	End-to-End Entity Linking and Disambiguation leveraging Word and Knowledge Graph Embeddings. CoRR Rostislav Nedelchev, Debanjan Chaudhuri, Jens Lehmann, Asja Fischer
2020	J	`jnl`	Improving the Long-Range Performance of Gated Graph Neural Networks. CoRR Denis Lukovnikov, Jens Lehmann, Asja Fischer
2020	J	`jnl`	Investigating maximum likelihood based training of infinite mixtures for uncertainty quantification. CoRR Sina Däubener, Asja Fischer
2020	A*	`conf`	Leveraging Frequency Analysis for Deep Fake Image Recognition. ICML Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, Thorsten Holz
2020	J	`jnl`	Leveraging Frequency Analysis for Deep Fake Image Recognition. CoRR Joel Frank, Thorsten Eisenhofer, Lea Schönherr, Asja Fischer, Dorothea Kolossa, Thorsten Holz
2020	J	`jnl`	Mimicking the radiologists' workflow: Estimating pediatric hand bone age with stacked deep neural networks. Medical Image Anal. Sven Koitka, Moon S. Kim, Ming Qu, Asja Fischer, Christoph M. Friedrich, Felix Nensa
2020	J	`jnl`	On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions. CoRR Kai Brügge, Asja Fischer, Christian Igel
2020	J	`jnl`	Pretrained Transformers for Simple Question Answering over Knowledge Graphs. CoRR Denis Lukovnikov, Asja Fischer, Jens Lehmann
2020	J	`jnl`	Second-Moment Loss: A Novel Regression Objective for Improved Uncertainties. CoRR Joachim Sicking, Maram Akila, Maximilian Pintz, Tim Wirtz, Asja Fischer, Stefan Wrobel
2020	J	`jnl`	Thresholded Adaptive Validation: Tuning the Graphical Lasso for Graph Recovery. CoRR Mike Laszkiewicz, Asja Fischer, Johannes Lederer
2020	J	`jnl`	Unsupervised Cross-Domain Speech-to-Speech Conversion with Time-Frequency Consistency. CoRR Mohammad Asif Khan, Fabien Cardinaux, Stefan Uhlich, Marc Ferras, Asja Fischer
2019	—	`conf`	Incorporating Literals into Knowledge Graph Embeddings. ISWC (1) Agustinus Kristiadi, Mohammad Asif Khan, Denis Lukovnikov, Jens Lehmann, Asja Fischer
2019	J	`jnl`	Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs. CoRR Nilesh Chakraborty, Denis Lukovnikov, Gaurav Maheshwari, Priyansh Trivedi, Jens Lehmann, Asja Fischer
2019	—	`conf`	Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs. ISWC (1) Gaurav Maheshwari, Priyansh Trivedi, Denis Lukovnikov, Nilesh Chakraborty, Asja Fischer, Jens Lehmann
2019	—	`conf`	On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length. ICLR (Poster) Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
2019	J	`jnl`	Predictive Uncertainty Quantification with Compound Density Networks. CoRR Agustinus Kristiadi, Asja Fischer
2019	—	`conf`	Pretrained Transformers for Simple Question Answering over Knowledge Graphs. ISWC (1) Denis Lukovnikov, Asja Fischer, Jens Lehmann
2018	J	`jnl`	DNN's Sharpest Directions Along the SGD Trajectory. CoRR Stanislaw Jastrzebski, Zachary Kenton, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
2018	—	`conf`	Finding Flatter Minima with SGD. ICLR (Workshop) Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
2018	B	`conf`	Improving Response Selection in Multi-Turn Dialogue Systems by Incorporating Domain Knowledge. CoNLL Debanjan Chaudhuri, Agustinus Kristiadi, Jens Lehmann, Asja Fischer
2018	J	`jnl`	Improving Response Selection in Multi-turn Dialogue Systems. CoRR Debanjan Chaudhuri, Agustinus Kristiadi, Jens Lehmann, Asja Fischer
2018	J	`jnl`	Incorporating Literals into Knowledge Graph Embeddings. CoRR Agustinus Kristiadi, Mohammad Asif Khan, Denis Lukovnikov, Jens Lehmann, Asja Fischer
2018	J	`jnl`	Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs. CoRR Gaurav Maheshwari, Priyansh Trivedi, Denis Lukovnikov, Nilesh Chakraborty, Asja Fischer, Jens Lehmann
2018	—	`conf`	On the regularization of Wasserstein GANs. ICLR (Poster) Henning Petzka, Asja Fischer, Denis Lukovnikov
2018	J	`jnl`	Population-Contrastive-Divergence: Does consistency help with RBM training? Pattern Recognit. Lett. Oswin Krause, Asja Fischer, Christian Igel
2018	J	`jnl`	Translating Natural Language to SQL using Pointer-Generator Networks and How Decoding Order Matters. CoRR Denis Lukovnikov, Nilesh Chakraborty, Jens Lehmann, Asja Fischer
2018	—	`conf`	Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio. ICANN (3) Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
2017	A*	`conf`	A Closer Look at Memorization in Deep Networks. ICML 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	J	`jnl`	A Closer Look at Memorization in Deep Networks. CoRR 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	—	`conf`	Deep Nets Don't Learn via Memorization. ICLR (Workshop) David Krueger, Nicolas Ballas, Stanislaw Jastrzebski, Devansh Arpit, Maxinder S. Kanwal, Tegan Maharaj, Emmanuel Bengio, Asja Fischer, Aaron C. Courville
2017	J	`jnl`	Graph-based predictable feature analysis. Mach. Learn. Björn Weghenkel, Asja Fischer, Laurenz Wiskott
2017	A*	`conf`	Neural Network-based Question Answering over Knowledge Graphs on Word and Character Level. WWW Denis Lukovnikov, Asja Fischer, Jens Lehmann, Sören Auer
2017	J	`jnl`	On the regularization of Wasserstein GANs. CoRR Henning Petzka, Asja Fischer, Denis Lukovnikov
2017	J	`jnl`	STDP-Compatible Approximation of Backpropagation in an Energy-Based Model. Neural Comput. Yoshua Bengio, Thomas Mesnard, Asja Fischer, Saizheng Zhang, Yuhuai Wu
2017	J	`jnl`	Three Factors Influencing Minima in SGD. CoRR Stanislaw Jastrzebski, Zachary Kenton, Devansh Arpit, Nicolas Ballas, Asja Fischer, Yoshua Bengio, Amos J. Storkey
2016	A*	`conf`	Bidirectional Helmholtz Machines. ICML Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio
2016	J	`jnl`	Graph-based Predictable Feature Analysis. CoRR Björn Weghenkel, Asja Fischer, Laurenz Wiskott
2016	J	`jnl`	How to Center Deep Boltzmann Machines. J. Mach. Learn. Res. Jan Melchior, Asja Fischer, Laurenz Wiskott
2015	J	`jnl`	A bound for the convergence rate of parallel tempering for sampling restricted Boltzmann machines. Theor. Comput. Sci. Asja Fischer, Christian Igel
2015	J	`jnl`	An objective function for STDP. CoRR Yoshua Bengio, Thomas Mesnard, Asja Fischer, Saizheng Zhang, Yuhai Wu
2015	—	`conf`	Difference Target Propagation. ECML/PKDD (1) Dong-hyun Lee, Saizheng Zhang, Asja Fischer, Yoshua Bengio
2015	J	`jnl`	Population-Contrastive-Divergence: Does Consistency help with RBM training? CoRR Oswin Krause, Asja Fischer, Christian Igel
2015	J	`jnl`	Training Restricted Boltzmann Machines. Künstliche Intell. Asja Fischer
2015	J	`jnl`	Training opposing directed models using geometric mean matching. CoRR Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio
2014	J	`jnl`	Training restricted Boltzmann machines: An introduction. Pattern Recognit. Asja Fischer, Christian Igel
2013	—	`conf`	Approximation properties of DBNs with binary hidden units and real-valued visible units. ICML (1) Oswin Krause, Asja Fischer, Tobias Glasmachers, Christian Igel
2013	J	`jnl`	How to Center Binary Restricted Boltzmann Machines. CoRR Jan Melchior, Asja Fischer, Nan Wang, Laurenz Wiskott
2013	J	`jnl`	The flip-the-state transition operator for restricted Boltzmann machines. Mach. Learn. Kai Brügge, Asja Fischer, Christian Igel
2012	C	`conf`	An Introduction to Restricted Boltzmann Machines. CIARP Asja Fischer, Christian Igel
2011	J	`jnl`	Bounding the Bias of Contrastive Divergence Learning. Neural Comput. Asja Fischer, Christian Igel
2011	B	`conf`	Training RBMs based on the signs of the CD approximation of the log-likelihood derivatives. ESANN Asja Fischer, Christian Igel
2010	—	`conf`	Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines. ICANN (3) Asja Fischer, Christian Igel