Alert button
Picture for Mathias Kraus

Mathias Kraus

Alert button

chatIPCC: Grounding Conversational AI in Climate Science

Apr 11, 2023
Saeid Ashraf Vaghefi, Qian Wang, Veruska Muccione, Jingwei Ni, Mathias Kraus, Julia Bingler, Tobias Schimanski, Chiara Colesanti-Senni, Nicolas Webersinke, Christrian Huggel, Markus Leippold

Figure 1 for chatIPCC: Grounding Conversational AI in Climate Science
Figure 2 for chatIPCC: Grounding Conversational AI in Climate Science
Figure 3 for chatIPCC: Grounding Conversational AI in Climate Science
Figure 4 for chatIPCC: Grounding Conversational AI in Climate Science
Viaarxiv icon

Enhancing Large Language Models with Climate Resources

Mar 31, 2023
Mathias Kraus, Julia Anna Bingler, Markus Leippold, Tobias Schimanski, Chiara Colesanti Senni, Dominik Stammbach, Saeid Ashraf Vaghefi, Nicolas Webersinke

Figure 1 for Enhancing Large Language Models with Climate Resources
Viaarxiv icon

Towards Climate Awareness in NLP Research

May 16, 2022
Daniel Hershcovich, Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler, Markus Leippold

Figure 1 for Towards Climate Awareness in NLP Research
Figure 2 for Towards Climate Awareness in NLP Research
Figure 3 for Towards Climate Awareness in NLP Research
Figure 4 for Towards Climate Awareness in NLP Research
Viaarxiv icon

GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints

Apr 19, 2022
Patrick Zschech, Sven Weinzierl, Nico Hambauer, Sandra Zilker, Mathias Kraus

Figure 1 for GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
Figure 2 for GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
Figure 3 for GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
Figure 4 for GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
Viaarxiv icon

A Light in the Dark: Deep Learning Practices for Industrial Computer Vision

Jan 06, 2022
Maximilian Harl, Marvin Herchenbach, Sven Kruschel, Nico Hambauer, Patrick Zschech, Mathias Kraus

Figure 1 for A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
Figure 2 for A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
Figure 3 for A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
Figure 4 for A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
Viaarxiv icon

ClimateBert: A Pretrained Language Model for Climate-Related Text

Oct 22, 2021
Nicolas Webersinke, Mathias Kraus, Julia Anna Bingler, Markus Leippold

Figure 1 for ClimateBert: A Pretrained Language Model for Climate-Related Text
Figure 2 for ClimateBert: A Pretrained Language Model for Climate-Related Text
Figure 3 for ClimateBert: A Pretrained Language Model for Climate-Related Text
Figure 4 for ClimateBert: A Pretrained Language Model for Climate-Related Text
Viaarxiv icon

AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units

Feb 17, 2021
Yilmazcan Özyurt, Mathias Kraus, Tobias Hatt, Stefan Feuerriegel

Figure 1 for AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units
Figure 2 for AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units
Figure 3 for AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units
Figure 4 for AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units
Viaarxiv icon

Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences

Jul 19, 2019
Mathias Kraus, Stefan Feuerriegel

Figure 1 for Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
Figure 2 for Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
Figure 3 for Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
Figure 4 for Forecasting remaining useful life: Interpretable deep learning approach via variational Bayesian inferences
Viaarxiv icon

Improving Heart Rate Variability Measurements from Consumer Smartwatches with Machine Learning

Jul 17, 2019
Martin Maritsch, Caterina Bérubé, Mathias Kraus, Vera Lehmann, Thomas Züger, Stefan Feuerriegel, Tobias Kowatsch, Felix Wortmann

Figure 1 for Improving Heart Rate Variability Measurements from Consumer Smartwatches with Machine Learning
Viaarxiv icon