Prof. Dr. Asja Fischer

Full Professor
Faculty of Mathematics
Ruhr-Universität Bochum

Profiles: LinkedIn, Google Scholar, DBLP

Office: IB 3/153
Universitätsstraße 150
44801 Bochum, Germany

Short CV


Note: I recently moved to Ruhr-University Bochum where I am Assistant Professor for Machine Learning now! I am still looking for a PhD student 🙂


Dr. Asja Fischer is a Assistant Professor at the Computer Science Department III of the University of Bonn. Before, she was a post-doctoral researcher at the Montreal Institute for Machine Learning (MILA). Between 2010 and end of 2014, Asja was employed both at the Institute for Neural Computation at the Ruhr-University Bochum and the Department of Computer Science at the University of Copenhagen working on her PhD in Machine Learning, which she defended in Copenhagen in 2014. Before, she studied Biology. Bioinformatics, Mathematics and Cognitive Science at the Ruhr-University Bochum, the Universidade de Lisboa and the University of Osnabrück.

Research Interests


  • Machine Learning
  • Deep Learning
  • Probabilistic Models
  • Sampling Techniques
  • Big Data

Teaching


Winter 2017

  • Lecture “Knowledge Graph Analysis”
  • Exercise “Knowledge Graph Analysis”
  • Seminar “Knowledge Graph Analysis”

Summer 2017

  • Lab “Deep Learning”
  • Seminar “Deep Learning”

Winter 2016

  • Lecture “Knowledge Graph Analysis”
  • Exercise “Knowledge Graph Analysis”
  • Seminar “Knowledge Graph Analysis”

Publications

2020

Krause, Oswin; Fischer, Asja; Igel, Christian

Algorithms for estimating the partition function of restricted Boltzmann machines Journal Article

Artif. Intell., 278 , 2020.

Links | BibTeX

Krause, Oswin; Fischer, Asja; Igel, Christian

Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract) Inproceedings

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020, pp. 5045–5049, ijcai.org, 2020.

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Ali, Mehdi; Berrendorf, Max; Hoyt, Charles Tapley; Vermue, Laurent; Galkin, Mikhail; Sharifzadeh, Sahand; Fischer, Asja; Tresp, Volker; Lehmann, Jens

Bringing Light Into the Dark: A Large-scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework Miscellaneous

2020.

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Koitka, Sven; Kim, Moon S; Qu, Ming; Fischer, Asja; Friedrich, Christoph M; Nensa, Felix

Mimicking the radiologists' workflow: Estimating pediatric hand bone age with stacked deep neural networks Journal Article

Medical Image Anal., 64 , pp. 101743, 2020.

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Frank, Joel; Eisenhofer, Thorsten; Schönherr, Lea; Fischer, Asja; Kolossa, Dorothea; Holz, Thorsten

Leveraging Frequency Analysis for Đeep Fake Image Recognition Inproceedings

Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, pp. 3247–3258, PMLR, 2020.

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Däubener, Sina; Schönherr, Lea; Fischer, Asja; Kolossa, Dorothea

Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification Inproceedings

Interspeech 2020, 21st Annual Conference of the International Speech Communication Association, Virtual Event, Shanghai, China, 25-29 October 2020, pp. 4661–4665, ISCA, 2020.

Links | BibTeX

Frank, Joel; Eisenhofer, Thorsten; Schönherr, Lea; Fischer, Asja; Kolossa, Dorothea; Holz, Thorsten

Leveraging Frequency Analysis for Deep Fake Image Recognition Inproceedings

Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, pp. 3247–3258, PMLR, 2020.

Links | BibTeX

2019

k e, Stanis{ł}aw Jastrz; Kenton, Zachary; Ballas, Nicolas; Fischer, Asja; Bengio, Yoshua; Storkey, Amos J

On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length Inproceedings

7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, OpenReview.net, 2019.

Links | BibTeX

Kristiadi, Agustinus; Khan, Mohammad Asif; Lukovnikov, Denis; Lehmann, Jens; Fischer, Asja

Incorporating Literals into Knowledge Graph Embeddings Inproceedings

The Semantic Web - ISWC 2019 - 18th International Semantic Web Conference, Auckland, New Zealand, October 26-30, 2019, Proceedings, Part I, pp. 347–363, Springer, 2019.

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Maheshwari, Gaurav; Trivedi, Priyansh; Lukovnikov, Denis; Chakraborty, Nilesh; Fischer, Asja; Lehmann, Jens

Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs Inproceedings

The Semantic Web - ISWC 2019 - 18th International Semantic Web Conference, Auckland, New Zealand, October 26-30, 2019, Proceedings, Part I, pp. 487–504, Springer, 2019.

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Lukovnikov, Denis; Fischer, Asja; Lehmann, Jens

Pretrained Transformers for Simple Question Answering over Knowledge Graphs Inproceedings

The Semantic Web - ISWC 2019 - 18th International Semantic Web Conference, Auckland, New Zealand, October 26-30, 2019, Proceedings, Part I, pp. 470–486, Springer, 2019.

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2018

Chaudhuri, Debanjan; Kristiadi, Agustinus; Lehmann, Jens; Fischer, Asja

Improving Response Selection in Multi-Turn Dialogue Systems by Incorporating Domain Knowledge Inproceedings

Proceedings of the 22nd Conference on Computational Natural Language Learning, CoNLL 2018, Brussels, Belgium, October 31 - November 1, 2018, pp. 497–507, Association for Computational Linguistics, 2018.

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k e, Stanis{ł}aw Jastrz; Kenton, Zachary; Arpit, Devansh; Ballas, Nicolas; Fischer, Asja; Bengio, Yoshua; Storkey, Amos J

Width of Minima Reached by Stochastic Gradient Descent is Influenced by Learning Rate to Batch Size Ratio Inproceedings

Artificial Neural Networks and Machine Learning - ICANN 2018 - 27th International Conference on Artificial Neural Networks, Rhodes, Greece, October 4-7, 2018, Proceedings, Part III, pp. 392–402, Springer, 2018.

Links | BibTeX

k e, Stanis{ł}aw Jastrz; Kenton, Zachary; Arpit, Devansh; Ballas, Nicolas; Fischer, Asja; Bengio, Yoshua; Storkey, Amos J

Finding Flatter Minima with SGD Inproceedings

6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Workshop Track Proceedings, OpenReview.net, 2018.

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Petzka, Henning; Fischer, Asja; Lukovnikov, Denis

On the regularization of Wasserstein GANs Inproceedings

6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings, OpenReview.net, 2018.

Links | BibTeX

Krause, Oswin; Fischer, Asja; Igel, Christian

Population-Contrastive-Divergence: Does consistency help with RBM training? Journal Article

Pattern Recognit. Lett., 102 , pp. 1–7, 2018.

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2017

Krueger, David; Ballas, Nicolas; k e, Stanis{ł}aw Jastrz; Arpit, Devansh; Kanwal, Maxinder S; Maharaj, Tegan; Bengio, Emmanuel; Fischer, Asja; Courville, Aaron C

Deep Nets Don't Learn via Memorization Inproceedings

5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24-26, 2017, Workshop Track Proceedings, OpenReview.net, 2017.

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Arpit, Devansh; k e, Stanis{ł}aw Jastrz; Ballas, Nicolas; Krueger, David; Bengio, Emmanuel; Kanwal, Maxinder S; Maharaj, Tegan; Fischer, Asja; Courville, Aaron C; Bengio, Yoshua; Lacoste-Julien, Simon

A Closer Look at Memorization in Deep Networks Inproceedings

Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, 6-11 August 2017, pp. 233–242, PMLR, 2017.

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Lukovnikov, Denis; Fischer, Asja; Lehmann, Jens; Auer, Sören

Neural Network-based Question Answering over Knowledge Graphs on Word and Character Level Inproceedings

Proceedings of the 26th International Conference on World Wide Web, WWW 2017, Perth, Australia, April 3-7, 2017, pp. 1211–1220, ACM, 2017.

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Weghenkel, Björn; Fischer, Asja; Wiskott, Laurenz

Graph-based predictable feature analysis Journal Article

Mach. Learn., 106 (9-10), pp. 1359–1380, 2017.

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Bengio, Yoshua; Mesnard, Thomas; Fischer, Asja; Zhang, Saizheng; Wu, Yuhuai

STDP-Compatible Approximation of Backpropagation in an Energy-Based Model Journal Article

Neural Computation, 29 (3), pp. 555–577, 2017.

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2016

Bornschein, Jörg; Shabanian, Samira; Fischer, Asja; Bengio, Yoshua

Bidirectional Helmholtz Machines Inproceedings

Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pp. 2511–2519, JMLR.org, 2016.

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Melchior, Jan; Fischer, Asja; Wiskott, Laurenz

How to Center Deep Boltzmann Machines Journal Article

J. Mach. Learn. Res., 17 , pp. 99:1–99:61, 2016.

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2015

Lee, Dong-Hyun; Zhang, Saizheng; Fischer, Asja; Bengio, Yoshua

Difference Target Propagation Inproceedings

Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part I, pp. 498–515, Springer, 2015.

Links | BibTeX

Fischer, Asja

Training Restricted Boltzmann Machines Journal Article

KI, 29 (4), pp. 441–444, 2015.

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Fischer, Asja; Igel, Christian

A bound for the convergence rate of parallel tempering for sampling restricted Boltzmann machines Journal Article

Theor. Comput. Sci., 598 , pp. 102–117, 2015.

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2014

Fischer, Asja; Igel, Christian

Training restricted Boltzmann machines: An introduction Journal Article

Pattern Recognit., 47 (1), pp. 25–39, 2014.

Links | BibTeX

2013

Krause, Oswin; Fischer, Asja; Glasmachers, Tobias; Igel, Christian

Approximation properties of DBNs with binary hidden units and real-valued visible units Inproceedings

Proceedings of the 30th International Conference on Machine Learning, ICML 2013, Atlanta, GA, USA, 16-21 June 2013, pp. 419–426, JMLR.org, 2013.

Links | BibTeX

Brügge, Kai; Fischer, Asja; Igel, Christian

The flip-the-state transition operator for restricted Boltzmann machines Journal Article

Mach. Learn., 93 (1), pp. 53–69, 2013.

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2012

Fischer, Asja; Igel, Christian

An Introduction to Restricted Boltzmann Machines Inproceedings

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications - 17th Iberoamerican Congress, CIARP 2012, Buenos Aires, Argentina, September 3-6, 2012. Proceedings, pp. 14–36, Springer, 2012.

Links | BibTeX

2011

Fischer, Asja; Igel, Christian

Training RBMs based on the signs of the CD approximation of the log-likelihood derivatives Inproceedings

ESANN 2011, 19th European Symposium on Artificial Neural Networks, Bruges, Belgium, April 27-29, 2011, Proceedings, 2011.

Links | BibTeX

Fischer, Asja; Igel, Christian

Bounding the Bias of Contrastive Divergence Learning Journal Article

Neural Computation, 23 (3), pp. 664–673, 2011.

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2010

Fischer, Asja; Igel, Christian

Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines Inproceedings

Artificial Neural Networks - ICANN 2010 - 20th International Conference, Thessaloniki, Greece, September 15-18, 2010, Proceedings, Part III, pp. 208–217, Springer, 2010.

Links | BibTeX