Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Kienzler, Romeo"'
Autor:
Schmude, Johannes, Roy, Sujit, Trojak, Will, Jakubik, Johannes, Civitarese, Daniel Salles, Singh, Shraddha, Kuehnert, Julian, Ankur, Kumar, Gupta, Aman, Phillips, Christopher E, Kienzler, Romeo, Szwarcman, Daniela, Gaur, Vishal, Shinde, Rajat, Lal, Rohit, Da Silva, Arlindo, Diaz, Jorge Luis Guevara, Jones, Anne, Pfreundschuh, Simon, Lin, Amy, Sheshadri, Aditi, Nair, Udaysankar, Anantharaj, Valentine, Hamann, Hendrik, Watson, Campbell, Maskey, Manil, Lee, Tsengdar J, Moreno, Juan Bernabe, Ramachandran, Rahul
Triggered by the realization that AI emulators can rival the performance of traditional numerical weather prediction models running on HPC systems, there is now an increasing number of large AI models that address use cases such as forecasting, downs
Externí odkaz:
http://arxiv.org/abs/2409.13598
Image retrieval enables an efficient search through vast amounts of satellite imagery and returns similar images to a query. Deep learning models can identify images across various semantic concepts without the need for annotations. This work propose
Externí odkaz:
http://arxiv.org/abs/2403.02059
Autor:
Kienzler, Romeo, Tizzei, Leonardo Pondian, Blumenstiel, Benedikt, Nagy, Zoltan Arnold, Mukkavilli, S. Karthik, Schmude, Johannes, Freitag, Marcus, Behrendt, Michael, Civitarese, Daniel Salles, Simumba, Naomi, Kimura, Daiki, Hamann, Hendrik
Storing and streaming high dimensional data for foundation model training became a critical requirement with the rise of foundation models beyond natural language. In this paper we introduce TensorBank, a petabyte scale tensor lakehouse capable of st
Externí odkaz:
http://arxiv.org/abs/2309.02094
In modern data-driven science, reproducibility and reusability are key challenges. Scientists are well skilled in the process from data to publication. Although some publication channels require source code and data to be made accessible, rerunning a
Externí odkaz:
http://arxiv.org/abs/2307.06824
Autor:
Kienzler, Romeo, Nesic, Ivan
Deep Learning models are getting more and more popular but constraints on explainability, adversarial robustness and fairness are often major concerns for production deployment. Although the open source ecosystem is abundant on addressing those conce
Externí odkaz:
http://arxiv.org/abs/2103.03281
Autor:
Issa, Shadi A.1, Kienzler, Romeo2, El-Kalioby, Mohamed1, Tonellato, Peter J.3, Wall, Dennis3, Bruggmann, Rémy4 remy.bruggmann@biology.unibe.ch, Abouelhoda, Mohamed1,5 mabouelhoda@yahoo.com
Publikováno v:
BioMed Research International. 2013, Vol. 2013, p1-16. 16p.
Publikováno v:
2012 IEEE 28th International Conference on Data Engineering Workshops; 1/ 1/2012, p159-166, 8p
Publikováno v:
Euro-Par 2011: Parallel Processing Workshops; 2012, p467-476, 10p