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We extend the concept of self-consistency for the Fokker-Planck equation (FPE) [Shen et al., 2022] to the more general McKean-Vlasov equation (MVE). While FPE describes the macroscopic behavior of par...
This report consists of two parts associated with graph neural networks: generalization and graph structural learning. We first study the Rademacher complexity of GNNs, as one of independent-algorithm...
We explore time-varying networks for high-dimensional locally stationary time series, using the large VAR model framework with both the transition and (error) precision matrices evolving smoothly over...
Deep neural networks, as a powerful system to represent high dimensional complex functions, play a key role in deep learning. Convergence of deep neural networks is a fundamental issue in building the...
Engineers at Caltech have shown that atoms in optical cavities -- tiny boxes for light -- could lead to the creation of a quantum internet. Their National Science Foundation-funded work...
Nowadays, graph symmetries are becoming a very important and rapidly growing area of study, and often looked at closely by computer scientists and other network designers. One significant instance of ...
Nowadays, graph symmetries are becoming a very important and rapidly growing area of study, and often looked at closely by computer scientists and other network designers. One significant instance of ...
The program aims at showing the role of modern statistical methods in complex data and serves to support interactions among mathematicians, statisticians, engineers and scientists working in the inter...
Multi-Beam Antennas (MBAs) find application in several fields including wireless and satellite communications, RADARs for electronic surveillance and remote sensing, science (e.g. radio telescopes), R...
Biodiversity loss is one of the driving factors in ecosystem change, on par with climate change and human development. When one species, especially a large predator, disappears from an area, other pop...
The Gordon Research Seminar on Posttranslational Modification Networks is a unique forum for graduate students, post-docs, and other scientists with comparable levels of experience and education to pr...
In the decades following the work by physiologist Ivan Pavlov and his famous salivating dogs, scientists have discovered how molecules and cells in the brain learn to associate two stimuli, like Pavlo...
We are pleased to announce the fifth Cold Spring Harbor Laboratory meeting on Systems Biology: Networks. The meeting will begin on the evening of Tuesday, March 14, 2017, and end after lunch on Saturd...
The 2017 Gordon Conference on Posttranslational Modification Networks will present the latest development on approaches how the protein machinery and signaling pathways function in the context of vari...
The 2017 Gordon Conference on Posttranslational Modification Networks will present the latest development on approaches how the protein machinery and signaling pathways function in the context of vari...

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