Journal ArticleDOI
The Mathematical Theory of Optimal Processes
Richard Bellman,L. S. Pontryagin,V. G. Boltyanskii,Revaz Valerianovich Gamkrelidze,E. F. Mishchenko,K. N. Trirogoff,Lucien W. Neustadt +6 more
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This article is published in Econometrica.The article was published on 1965-01-01. It has received 4391 citations till now. The article focuses on the topics: Mathematical theory.read more
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Deep learning in neural networks
TL;DR: This historical survey compactly summarizes relevant work, much of it from the previous millennium, review deep supervised learning, unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
Book
Principles of Robot Motion: Theory, Algorithms, and Implementations
Howie Choset,Jean-Claude Latombe +1 more
TL;DR: In this paper, the mathematical underpinnings of robot motion are discussed and a text that makes the low-level details of implementation to high-level algorithmic concepts is presented.
Journal ArticleDOI
The theory of variational hybrid quantum-classical algorithms
TL;DR: Peruzzo et al. as mentioned in this paper developed a variational adiabatic ansatz and explored unitary coupled cluster where they established a connection from second order unitary cluster to universal gate sets through a relaxation of exponential operator splitting.
Book ChapterDOI
Preference, production, and capital: Optimum technical change in an aggregative model of economic growth
Hirofumi Uzawa,Kenneth J. Arrow +1 more
Proceedings Article
Neural ordinary differential equations
TL;DR: In this paper, the authors introduce a new family of deep neural network models called continuous normalizing flows, which parameterize the derivative of the hidden state using a neural network, and the output of the network is computed using a black-box differential equation solver.