Zobrazeno 1 - 10
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pro vyhledávání: '"Levina AS"'
A number of models have been developed for information spread through networks, often for solving the Influence Maximization (IM) problem. IM is the task of choosing a fixed number of nodes to "seed" with information in order to maximize the spread o
Externí odkaz:
http://arxiv.org/abs/2411.09100
Networks arise naturally in many scientific fields as a representation of pairwise connections. Statistical network analysis has most often considered a single large network, but it is common in a number of applications, for example, neuroimaging, to
Externí odkaz:
http://arxiv.org/abs/2410.17046
In network settings, interference between units makes causal inference more challenging as outcomes may depend on the treatments received by others in the network. Typical estimands in network settings focus on treatment effects aggregated across ind
Externí odkaz:
http://arxiv.org/abs/2410.11797
Timescales of neural activity are diverse across and within brain areas, and experimental observations suggest that neural timescales reflect information in dynamic environments. However, these observations do not specify how neural timescales are sh
Externí odkaz:
http://arxiv.org/abs/2409.02684
Autor:
Hamidi, Mani, Khajehabdollahi, Sina, Giannakakis, Emmanouil, Schäfer, Tim, Levina, Anna, Wu, Charley M.
Structural modularity is a pervasive feature of biological neural networks, which have been linked to several functional and computational advantages. Yet, the use of modular architectures in artificial neural networks has been relatively limited des
Externí odkaz:
http://arxiv.org/abs/2406.06262
Autor:
Susobhanan, Abhimanyu, Kaplan, David, Archibald, Anne, Luo, Jing, Ray, Paul, Pennucci, Timothy, Ransom, Scott, Agazie, Gabriella, Fiore, William, Larsen, Bjorn, O'Neill, Patrick, van Haasteren, Rutger, Anumarlapudi, Akash, Bachetti, Matteo, Bhakta, Deven, Champagne, Chloe, Cromartie, H. Thankful, Demorest, Paul, Jennings, Ross, Kerr, Matthew, Levina, Sasha, McEwen, Alexander, Shapiro-Albert, Brent, Swiggum, Joseph
PINT is a pure-Python framework for high-precision pulsar timing developed on top of widely used and well-tested Python libraries, supporting both interactive and programmatic data analysis workflows. We present a new frequentist framework within PIN
Externí odkaz:
http://arxiv.org/abs/2405.01977
Autor:
Levina, Kristina, Pappas, Nikolaos, Karapantelakis, Athanasios, Feljan, Aneta Vulgarakis, Seipp, Jendrik
Reward machines inform reinforcement learning agents about the reward structure of the environment and often drastically speed up the learning process. However, reward machines only accept Boolean features such as robot-reached-gold. Consequently, ma
Externí odkaz:
http://arxiv.org/abs/2404.19370
Many settings in machine learning require the selection of a rotation representation. However, choosing a suitable representation from the many available options is challenging. This paper acts as a survey and guide through rotation representations.
Externí odkaz:
http://arxiv.org/abs/2404.11735
Developing reliable mechanisms for continuous local learning is a central challenge faced by biological and artificial systems. Yet, how the environmental factors and structural constraints on the learning network influence the optimal plasticity mec
Externí odkaz:
http://arxiv.org/abs/2403.13649
Autor:
Halaburda, Hanna (AUTHOR) hh66@stern.nyu.edu, Levina, Natalia (AUTHOR) nl28@stern.nyu.edu, Semi Min (AUTHOR) minxx146@umn.edu
Publikováno v:
MIS Quarterly. Jun2024, Vol. 48 Issue 2, p825-846. 22p. 1 Diagram, 6 Charts.
