{"id":3328,"date":"2017-11-25T13:10:43","date_gmt":"2017-11-25T13:10:43","guid":{"rendered":"https:\/\/hci.iwr.uni-heidelberg.de\/vislearn\/?page_id=3328"},"modified":"2022-04-01T08:23:21","modified_gmt":"2022-04-01T08:23:21","slug":"jakob-kruse","status":"publish","type":"page","link":"https:\/\/hci.iwr.uni-heidelberg.de\/vislearn\/people\/jakob-kruse\/","title":{"rendered":"Jakob Kruse"},"content":{"rendered":"

<\/p>\n

Jakob Kruse<\/h2>\n

Doctoral student at Visual Learning Lab Heidelberg
\nMathematikon B, room A117<\/p>\n

Email:<\/b> jakob.kruse (at) iwr.uni-heidelberg.de
\nPhone:<\/b> +49 6221 54 14887 (shared)<\/i>
\nAddress:<\/b>
\nIWR, Uni Heidelberg
\nBerliner Stra\u00dfe 43
\n69120 Heidelberg<\/p>\n

Google Scholar profile<\/a><\/b><\/p>\n

Publications<\/h2>\n

Jakob Kruse<\/u>. Technical report: Training Mixture Density Networks with full covariance matrices.<\/b> arXiv:2003.05739, March 2020.
\n[arXiv<\/a>] [Code<\/a>]<\/p>\n

Jakob Kruse<\/u>, Gianluca Detommaso, Robert Scheichl, Ullrich K\u00f6the. HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference.<\/b> arXiv:1905.10687, March 2020. (accepted at AAAI 2021)<\/i>
\n[arXiv<\/a>] [Poster<\/a>] [Slides<\/a>] [Talk<\/a>] [Previous version<\/a>] [Code<\/a>]<\/p>\n

Lynton Ardizzone, Carsten L\u00fcth, Jakob Kruse<\/u>, Carsten Rother, Ullrich K\u00f6the. Guided Image Generation with Conditional Invertible Neural Networks.<\/b> arXiv:1907.02392, July 2019.
\n[arXiv<\/a>] [Supplement<\/a>] [Code<\/a>]<\/p>\n

Jakob Kruse<\/u>, Lynton Ardizzone, Carsten Rother, Ullrich K\u00f6the. Benchmarking Invertible Architectures on Inverse Problems.<\/b> First Workshop on Invertible Neural Networks and Normalizing Flows (ICML 2019), Long Beach, USA, June 2019.
\n[Paper<\/a>] [Poster<\/a>] [Code coming]<\/p>\n

Tim J Adler, Lynton Ardizzone, Anant Vemuri, Leonardo Ayala, Janek Gr\u00f6hl, Thomas Kirchner, Sebastian Wirkert, Jakob Kruse<\/u>, Carsten Rother, Ullrich K\u00f6the, Lena Maier-Hein. Uncertainty-Aware Performance Assessment of Optical Imaging Modalities with Invertible Neural Networks.<\/b> International Journal of Computer Assisted Radiology and Surgery (IJCARS), 14:997, June 2019.
\n[SpringerLink<\/a>]<\/p>\n

Lynton Ardizzone, Jakob Kruse<\/u>, Sebastian Wirkert, Daniel Rahner, Eric W. Pellegrini, Ralf S. Klessen, Lena Maier-Hein, Carsten Rother, Ullrich K\u00f6the. Analyzing Inverse Problems with Invertible Neural Networks.<\/b> International Conference on Learning Representations (ICLR), New Orleans, USA, May 2019.
\n[OpenReview page<\/a>] [Poster<\/a>] [Code<\/a>] [Framework<\/a>]<\/p>\n

Jakob Kruse<\/u>, Carsten Rother and Uwe Schmidt. Learning to Push the Limits of Efficient FFT-based Image Deconvolution.<\/b> IEEE International Conference on Computer Vision (ICCV), Venice, Italy, October 2017.
\nSpotlight presentation.<\/i>
\n[Paper<\/a>] [Supplement<\/a>] [Poster<\/a>] [Spotlight Talk<\/a>] [Code<\/a>]<\/p>\n

Talks<\/h2>\n

Invertible Neural Networks as a tool for ill-posed inverse problems.<\/b> Bremen, September 2019.
\n[Slides<\/a>]<\/p>\n

Teaching<\/h2>\n

Bomberman Multi-agent Reinforcement Learning Environment.<\/b> For Fundamentals of Machine Learning WS 18\/19.
\n[Framework<\/a>] [2019 tournament results<\/a>]<\/p>\n

Theses<\/h2>\n

Comparison of Learned Inference Approaches for Image Restoration.<\/b> Master’s Thesis, September 2016.
\nGraded 1.0<\/i>
\n[Thesis<\/a>] [Slides<\/a>]<\/p>\n

Steganalyse einer Erweiterung des steganographischen Algorithmus HUGO.<\/b> Bachelor’s Thesis, April 2013.
\nGraded 1.2<\/i>
\n[Thesis<\/a>] (German)<\/p>\n

Misc<\/h2>\n

Super-Resolution with Regression Tree Fields.<\/b> Lab Course, May 2015.
\n[Report<\/a>]<\/p>\n

Looped mathsy animations.<\/b> Just a hobby \ud83d\ude42
\n[Gallery<\/a>] [Instagram<\/a>] [Public code<\/a>]<\/p>\n

Critically endangered species.<\/b>
\n[Gallery<\/a>] [Video<\/a>]<\/p>\n

\n

We are currently witnessing the 6th mass extinction event<\/a> in our planet’s history.<\/p>\n

Modern civilization is under legitimate threat<\/a> by runaway climate change<\/a>. This is real.<\/p>\n

We are the first generation that will feel the effect, and the last who can still stop it. But we need to take radical action now!<\/p>\n

Please consider joining the peaceful rebellion<\/a>, or any other movement fighting to fix this broken system. There is a very active Heidelberg branch<\/a> as well.<\/b><\/p>\n

Contact me if you would like to know more.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Jakob Kruse Doctoral student at Visual Learning Lab Heidelberg Mathematikon B, room A117 Email: jakob.kruse (at) iwr.uni-heidelberg.de Phone: +49 6221 54 14887 (shared) Address: IWR, Uni Heidelberg Berliner Stra\u00dfe 43 69120 Heidelberg Google Scholar profile Publications Jakob Kruse. Technical report: Training Mixture Density Networks with full covariance matrices. arXiv:2003.05739, March 2020. [arXiv] [Code] Jakob Kruse, […]<\/p>\n","protected":false},"author":6,"featured_media":0,"parent":80,"menu_order":2,"comment_status":"closed","ping_status":"closed","template":"templates\/template-full-notitle.php","meta":{"inline_featured_image":false,"footnotes":""},"class_list":["post-3328","page","type-page","status-publish","hentry","post"],"yoast_head":"\nJakob Kruse | Visual Learning Lab Heidelberg<\/title>\n<meta name=\"description\" content=\"PhD student with Dr. Ullrich K\u00f6the and Prof. Dr. Carsten Rother. 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