2 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Carnegie Mellon UniversityUS3 papers
- Center for Strategic ResearchRU3 papers
- Machine ScienceUS3 papers
- Robotic Research (United States)US3 papers
- Stanford UniversityUS2 papers
- Applied Optimization (United States)US1 paper
- Boston CollegeUS1 paper
- Brown UniversityUS1 paper
- California University of PennsylvaniaUS1 paper
- Colby CollegeUS1 paper
- Columbia UniversityUS1 paper
- Convergent Engineering (United States)US1 paper
5 papers
Multi-objective CFD optimization of an intermediate diffuser stage for PediaFlow pediatric ventricular assist device
Mansur Zhussupbekov, JingChun Wu, Greg W Burgreen +3
Background: Computational fluid dynamics (CFD) has become an essential design tool for ventricular assist devices (VADs), where the goal of maximizing performance often conflicts w…
Joint-perturbation simultaneous pseudo-gradient
Carlos Martin, Tuomas Sandholm
We study the problem of computing an approximate Nash equilibrium of a game whose strategy space is continuous without access to gradients of the utility function. Such games arise…
Layered Graph Security Games
Jakub Černý, Chun Kai Ling, Christian Kroer +1
Security games model strategic interactions in adversarial real-world applications. Such applications often involve extremely large but highly structured strategy sets (e.g., selec…
Temporal Graph ODEs for Irregularly-Sampled Time Series
Alessio Gravina, Daniele Zambon, Davide Bacciu +1
Modern graph representation learning works mostly under the assumption of dealing with regularly sampled temporal graph snapshots, which is far from realistic, e.g., social network…
The time is ripe to reverse engineer an entire nervous system: simulating behavior from neural interactions
Gal Haspel, Ben Baker, Isabel Beets +34
Just like electrical engineers understand how microprocessors execute programs in terms of how transistor currents are affected by their inputs, neuroscientists want to understand…