Zobrazeno 1 - 10
of 2 572
pro vyhledávání: '"Klemmer, A"'
Extending knowledge by identifying and investigating valuable research questions and problems is a core function of research. Research publications often suggest avenues for future work to extend and build upon their results. Considering these sugges
Externí odkaz:
http://arxiv.org/abs/2405.20785
Autor:
Klemmer, Jan H., Horstmann, Stefan Albert, Patnaik, Nikhil, Ludden, Cordelia, Burton Jr., Cordell, Powers, Carson, Massacci, Fabio, Rahman, Akond, Votipka, Daniel, Lipford, Heather Richter, Rashid, Awais, Naiakshina, Alena, Fahl, Sascha
Following the recent release of AI assistants, such as OpenAI's ChatGPT and GitHub Copilot, the software industry quickly utilized these tools for software development tasks, e.g., generating code or consulting AI for advice. While recent research ha
Externí odkaz:
http://arxiv.org/abs/2405.06371
Autor:
Klemmer, Kerry S., Howland, Michael F.
To achieve decarbonization targets, wind turbines are growing in hub height, rotor diameter, and are being deployed in new locations with diverse atmospheric conditions not previously seen, such as offshore. Physics-based analytical wake models commo
Externí odkaz:
http://arxiv.org/abs/2404.15117
Autor:
Klemmer, Nick, Fleper, Janek, Jonas, Valentin, Sheikhan, Ameneh, Kollath, Corinna, Köhl, Michael, Bergschneider, Andrea
We investigate the experimental control of pair tunneling in a double-well potential using Floquet engineering. We demonstrate a crossover from a regime with density-assisted tunneling to dominant pair tunneling by tuning the effective interactions.
Externí odkaz:
http://arxiv.org/abs/2404.08482
Satellite data has the potential to inspire a seismic shift for machine learning -- one in which we rethink existing practices designed for traditional data modalities. As machine learning for satellite data (SatML) gains traction for its real-world
Externí odkaz:
http://arxiv.org/abs/2402.01444
Autor:
Jordan, Jakob, Jaitner, Noah, Meyer, Tom, Brahmè, Luca, Ghrayeb, Mnar, Köppke, Julia, Chandia, Stefan Klemmer, Zaburdaev, Vasily, Chai, Liraz, Tzschätzsch, Heiko, Mura, Joaquin, Hagemann, Anja I. H., Braun, Jürgen, Sack, Ingolf
Rapid mapping of the mechanical properties of soft biological tissues from light microscopy to macroscopic imaging could transform fundamental biophysical research by providing clinical biomarkers to complement in vivo elastography. We here introduce
Externí odkaz:
http://arxiv.org/abs/2312.07380
Geographic information is essential for modeling tasks in fields ranging from ecology to epidemiology. However, extracting relevant location characteristics for a given task can be challenging, often requiring expensive data fusion or distillation fr
Externí odkaz:
http://arxiv.org/abs/2311.17179
Publikováno v:
Published as a conference paper at ICLR 2024
Learning representations of geographical space is vital for any machine learning model that integrates geolocated data, spanning application domains such as remote sensing, ecology, or epidemiology. Recent work embeds coordinates using sine and cosin
Externí odkaz:
http://arxiv.org/abs/2310.06743
Autor:
Klemmer, Jan H., Gutfleisch, Marco, Stransky, Christian, Acar, Yasemin, Sasse, M. Angela, Fahl, Sascha
Usable and secure authentication on the web and beyond is mission-critical. While password-based authentication is still widespread, users have trouble dealing with potentially hundreds of online accounts and their passwords. Alternatives or extensio
Externí odkaz:
http://arxiv.org/abs/2309.00744
Autor:
Xu, Lily, Rolf, Esther, Beery, Sara, Bennett, Joseph R., Berger-Wolf, Tanya, Birch, Tanya, Bondi-Kelly, Elizabeth, Brashares, Justin, Chapman, Melissa, Corso, Anthony, Davies, Andrew, Garg, Nikhil, Gaylard, Angela, Heilmayr, Robert, Kerner, Hannah, Klemmer, Konstantin, Kumar, Vipin, Mackey, Lester, Monteleoni, Claire, Moorcroft, Paul, Palmer, Jonathan, Perrault, Andrew, Thau, David, Tambe, Milind
In this white paper, we synthesize key points made during presentations and discussions from the AI-Assisted Decision Making for Conservation workshop, hosted by the Center for Research on Computation and Society at Harvard University on October 20-2
Externí odkaz:
http://arxiv.org/abs/2307.08774