bridge problem
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Author(s):  
Soh Edwin Mukiawa

AbstractIn this paper, we study a plate equation as a model for a suspension bridge with time-varying delay and time-varying weights. Under some conditions on the delay and weight functions, we establish a stability result for the associated energy functional. The present work extends and generalizes some similar results in the case of wave or plate equations.


Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1134
Author(s):  
Francisco Vargas ◽  
Pierre Thodoroff ◽  
Austen Lamacraft ◽  
Neil Lawrence

The Schrödinger bridge problem (SBP) finds the most likely stochastic evolution between two probability distributions given a prior stochastic evolution. As well as applications in the natural sciences, problems of this kind have important applications in machine learning such as dataset alignment and hypothesis testing. Whilst the theory behind this problem is relatively mature, scalable numerical recipes to estimate the Schrödinger bridge remain an active area of research. Our main contribution is the proof of equivalence between solving the SBP and an autoregressive maximum likelihood estimation objective. This formulation circumvents many of the challenges of density estimation and enables direct application of successful machine learning techniques. We propose a numerical procedure to estimate SBPs using Gaussian process and demonstrate the practical usage of our approach in numerical simulations and experiments.


2021 ◽  
Vol 59 (4) ◽  
pp. 2428-2453
Author(s):  
Isabel Haasler ◽  
Axel Ringh ◽  
Yongxin Chen ◽  
Johan Karlsson

2020 ◽  
Vol 26 (6) ◽  
pp. 3313-3331
Author(s):  
Erick Jose Ramirez ◽  
Scott LaBarge

2020 ◽  
Vol 85 (2) ◽  
Author(s):  
Simone Di Marino ◽  
Augusto Gerolin

AbstractThis paper exploit the equivalence between the Schrödinger Bridge problem (Léonard in J Funct Anal 262:1879–1920, 2012; Nelson in Phys Rev 150:1079, 1966; Schrödinger in Über die umkehrung der naturgesetze. Verlag Akademie der wissenschaften in kommission bei Walter de Gruyter u, Company, 1931) and the entropy penalized optimal transport (Cuturi in: Advances in neural information processing systems, pp 2292–2300, 2013; Galichon and Salanié in: Matching with trade-offs: revealed preferences over competing characteristics. CEPR discussion paper no. DP7858, 2010) in order to find a different approach to the duality, in the spirit of optimal transport. This approach results in a priori estimates which are consistent in the limit when the regularization parameter goes to zero. In particular, we find a new proof of the existence of maximizing entropic-potentials and therefore, the existence of a solution of the Schrödinger system. Our method extends also when we have more than two marginals: the main new result is the proof that the Sinkhorn algorithm converges even in the continuous multi-marginal case. This provides also an alternative proof of the convergence of the Sinkhorn algorithm in two marginals.


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