Direkt zum Inhalt springen
Computer Vision Group
TUM School of Computation, Information and Technology
Technical University of Munich

Technical University of Munich

Menu

Links


Christian Tomani

PhD StudentTechnical University of Munich

School of Computation, Information and Technology
Informatics 9
Boltzmannstrasse 3
85748 Garching
Germany

Tel: +49-89-289-17779
Fax: +49-89-289-17757
Office: 02.09.037
Mail: christian.tomani@in.tum.de

Brief Bio

Find me on Linkedin and Google Scholar.

I am a PhD student at the Technical University of Munich at the Chair for Computer Vision and Artificial Intelligence headed by Prof. Daniel Cremers. I received my Master's degree from TUM and my Bachelor's degree from Technical University Graz and studied as well as conducted research at University of Oxford, University of California Berkeley and University of Agder.

My interests cover a large spectrum of Machine Learning and Deep Learning topics. Projects of mine include uncertainty aware and robust models for in domain, domain shift and out of domain (OOD) scenarios; Computer Vision (CV); Natural Language Processing (NLP); Time Series Data Analysis with supervised and self-supervised learning algorithms; Recurrent Neural Networks (RNNs) and Transformer architectures; attribution maps; designing learning algorithms for generalization; etc.

I am looking for motivated as well as talented students. If you are interested please contact me directly via email and highlight your relevant academic experience and programming skills. Additionally, please include a CV and a recent transcript.

Publications

  • Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration, ECCV 2022.


  • Post-hoc Uncertainty Calibration for Domain Drift Scenarios, CVPR 2021, Oral Presentation.



Export as PDF, XML, TEX or BIB

2022
Preprints
[]Challenger: Training with Attribution Maps (C Tomani and D Cremers), In arXiv preprint, 2022.  [bibtex] [arXiv:2205.15094] [pdf]
Conference and Workshop Papers
[]What Makes Graph Neural Networks Miscalibrated? (HHH Hsu, Y Shen, C Tomani and D Cremers), In NeurIPS, 2022. ([code]) [bibtex] [arXiv:2210.06391]
[]Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration (C Tomani, D Cremers and F Buettner), In European Conference on Computer Vision (ECCV), 2022.  [bibtex] [arXiv:2102.12182]
2021
Conference and Workshop Papers
[]Post-hoc Uncertainty Calibration for Domain Drift Scenarios (C Tomani, S Gruber, ME Erdem, D Cremers and F Buettner), In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021.  [bibtex] [arXiv:2012.10988]Oral Presentation
[]Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration (C Tomani and F Buettner), In InThirty-FifthAAAIConferenceonArtificialIntelligence(AAAI-2021), 2021.  [bibtex] [arXiv:2012.10923]
Powered by bibtexbrowser
Export as PDF, XML, TEX or BIB

Rechte Seite

Informatik IX
Computer Vision Group

Boltzmannstrasse 3
85748 Garching info@vision.in.tum.de

Follow us on:

News

15.10.2022

NeurIPS 2022

We have two papers accepted to NeurIPS 2022.

15.10.2022

WACV 2023

We have two papers accepted at WACV 2023.

31.08.2022

Fulbright PULSE podcast on Prof. Cremers went online on Apple Podcasts and Spotify.

17.07.2022

MCML Kick-Off

On July 27th, we are organizing the Kick-Off of the Munich Center for Machine Learning in the Bavarian Academy of Sciences.

17.07.2022

AI Symposium

On July 22nd 2022, we are organizing a Symposium on AI within the Technology Forum of the Bavarian Academy of Sciences.

More