Zobrazeno 1 - 10
of 19 091
pro vyhledávání: '"A, Keyser"'
Autor:
Hänni, Nora, Altwegg, Kathrin, Combi, Michael, Fuselier, Stephen A., De Keyser, Johan, Ligterink, Niels F. W., Rubin, Martin, Wampfler, Susanne F.
Technological progress related to astronomical observatories such as the recently launched James Webb Space Telescope (JWST) allows searching for signs of life beyond our Solar System, namely in the form of unambiguous biosignature gases in exoplanet
Externí odkaz:
http://arxiv.org/abs/2410.08724
Autor:
Frew, Jack, Keyser, Nigel, Kim, Ethan, Paddock, Griffin, Toumbleston, Camden, Wilson, Sara, Tsikkou, Charis
We consider a system of two balance laws of Keyfitz-Kranzer type with varying generalized Chaplygin gas, which exhibits negative pressure and is a product of a function of time and the inverse of a power of the density. The Chaplygin gas is a fluid d
Externí odkaz:
http://arxiv.org/abs/2407.20869
Autor:
Zheng, Fei, Suma, Antonio, Maffeo, Christopher, Chen, Kaikai, Alawami, Mohammed, Sha, Jingjie, Aksimentiev, Aleksei, Micheletti, Cristian, Keyser, Ulrich F
The transport of DNA polymers through nanoscale pores is central to many biological processes, from bacterial gene exchange to viral infection. In single-molecule nanopore sensing, the detection of nucleic acid and protein analytes relies on the pass
Externí odkaz:
http://arxiv.org/abs/2407.16290
Optical motion capture (mocap) requires accurately reconstructing the human body from retroreflective markers, including pose and shape. In a typical mocap setting, marker labeling is an important but tedious and error-prone step. Previous work has s
Externí odkaz:
http://arxiv.org/abs/2407.06114
Autor:
De Keyser, Steven, Gijbels, Irene
We generalize 2-Wasserstein dependence coefficients to measure dependence between a finite number of random vectors. This generalization includes theoretical properties, and in particular focuses on an interpretation of maximal dependence and an asym
Externí odkaz:
http://arxiv.org/abs/2404.07141
Autor:
Jain, Ajit, Kerne, Andruid, Lupfer, Nic, Britain, Gabriel, Perrine, Aaron, Choe, Yoonsuck, Keyser, John, Huang, Ruihong, Seo, Jinsil, Sungkajun, Annie, Lightfoot, Robert, McGuire, Timothy
We investigate how to use AI-based analytics to support design education. The analytics at hand measure multiscale design, that is, students' use of space and scale to visually and conceptually organize their design work. With the goal of making the
Externí odkaz:
http://arxiv.org/abs/2404.05417
Autor:
Thorneywork, Alice L., Gladrow, Jannes, Keyser, Ulrich F., Cates, Michael E., Adhikari, Ronojoy, Kappler, Julian
Recent experiments have probed the relative likelihoods of trajectories in stochastic systems by observing survival probabilities within a tube of radius $R$ in spacetime. We measure such probabilities here for a colloidal particle in a corrugated ch
Externí odkaz:
http://arxiv.org/abs/2402.01559
Autor:
Lin, Guying, Yang, Lei, Liu, Yuan, Zhang, Congyi, Hou, Junhui, Jin, Xiaogang, Komura, Taku, Keyser, John, Wang, Wenping
Neural implicit fields, such as the neural signed distance field (SDF) of a shape, have emerged as a powerful representation for many applications, e.g., encoding a 3D shape and performing collision detection. Typically, implicit fields are encoded b
Externí odkaz:
http://arxiv.org/abs/2401.01391
Autor:
Rubin, Martin, Altwegg, Kathrin, Berthelier, Jean-Jacques, Combi, Michael R., De Keyser, Johan, Fuselier, Stephen A., Gombosi, Tamas I., Gudipati, Murthy S., Hänni, Nora, Kipfer, Kristina A., Ligterink, Niels F. W., Müller, Daniel R., Shou, Yinsi, Wampfler, Susanne F.
Publikováno v:
Monthly Notices of the Royal Astronomical Society, stad3005, 2023
ESA's Rosetta spacecraft at comet 67P/Churyumov-Gerasimenko (67P) was the first mission that accompanied a comet over a substantial fraction of its orbit. On board was the ROSINA mass spectrometer suite to measure the local densities of the volatile
Externí odkaz:
http://arxiv.org/abs/2310.04095
Autor:
Yang, Lei, Liang, Yongqing, Li, Xin, Zhang, Congyi, Lin, Guying, Sheffer, Alla, Schaefer, Scott, Keyser, John, Wang, Wenping
The recent surge of utilizing deep neural networks for geometric processing and shape modeling has opened up exciting avenues. However, there is a conspicuous lack of research efforts on using powerful neural representations to extend the capabilitie
Externí odkaz:
http://arxiv.org/abs/2309.09911