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Showing 1 to 13 of 13 for “"Tensor train"”.

  1. A tensor-train-decomposition-based algorithm for high-dimensional pursuit-evasion games

    … under certain circumstances by utilizing tensor-train (TT) decomposition. By using this intuition, a new algorithm for solving high dimensional pursuit-evasion problems called Best-Response Tensor-Train-decomposition-based Value Iteration (BR-TT-VI) was developed. BR-TT-VI builds on …

    mit Repository record for A tensor-train-decomposition-based algorithm for high-dimensional pursuit-evasion games (opens in a new tab)

  2. Automated synthesis of low-rank stochastic dynamical systems using the tensor-train decomposition

    … behavior. The tight coupling of physical constraints and computation that typically characterize cyber-physical systems make them extremely complex, resulting in unexpected failure modes. Furthermore, disturbances in the environment and uncertainties in the physical model require these systems …

    mit Repository record for Automated synthesis of low-rank stochastic dynamical systems using the tensor-train decomposition (opens in a new tab)

  3. Analysis of Continuous Tensor-Train Methods for Optimal Control Problems with the Ornstein-Uhlenbeck Operator

    Continuous tensor-train decompositions methods have been found to well approximate optimal control policies under certain conditions for dynamic programming problems within the Compressed Continuous Computation (C3) framework. We aim to utilize numerically approximated control solutions found using …

    mit Repository record for Analysis of Continuous Tensor-Train Methods for Optimal Control Problems with the Ornstein-Uhlenbeck Operator (opens in a new tab)

  4. Continuous low-rank tensor decompositions, with applications to stochastic optimal control and data assimilation

    … framework tightly integrates two emerging areas: tensor decompositions and continuous computation. Tensor decompositions are able to effectively compress and operate with low-rank multidimensional arrays. Continuous computation is a paradigm for computing with functions instead of arrays, and it …

    mit Repository record for Continuous low-rank tensor decompositions, with applications to stochastic optimal control and data assimilation (opens in a new tab)

  5. Quantics Tensor Trains: The Study of a Continuous Lattice Model and Beyond

    … of continuous variable functions with tensor train representation. The first chapter describes all the methodology used to discretize functions and store them efficiently. In this section, the algorithm tensor renormalization group is explained for self-containment purposes. The second …

    cuny-grad Repository record for Quantics Tensor Trains: The Study of a Continuous Lattice Model and Beyond (opens in a new tab)

  6. Guidance laws for partially-observable UAV interception based on linear covariance analysis

    … optimal controller is calculated in compressed tensor train (TT) format. By compressing the state space, it is possible to calculate the optimal control action at any state in real time. A set of observability maneuvers is identified to help the pursuer improve the estimate quality of an …

    mit Repository record for Guidance laws for partially-observable UAV interception based on linear covariance analysis (opens in a new tab)

  7. Agile quadrotor maneuvering using tensor-decomposition-based globally optimal control and onboard visual-inertial estimation

    … resulting optimization problem is solved using tensor-train-decomposition-based compressed continuous computation techniques. The platform's capabilities and the potential of these types of controllers are demonstrated in both simulation studies and in experiments.

    mit Repository record for Agile quadrotor maneuvering using tensor-decomposition-based globally optimal control and onboard visual-inertial estimation (opens in a new tab)

  8. Functional analysis of low grade glioma genetic variants using statistics and physics-inspired deep learning methods

    … interpretation methods. Finally, we applied tensor train decomposition (TT-decomposition) to neural network parameter reduction and demonstrated that the reduced convolutional neural network performed well. This work helps understand the molecular mechanisms underlying genetic risk factors of …

    uiuc Repository record for Functional analysis of low grade glioma genetic variants using statistics and physics-inspired deep learning methods (opens in a new tab)

  9. Themes in numerical tensor calculus

    … distinct, but related, aspects of numerical tensor calculus. First, we introduce a simple, black-box compression format for tensors with a multiscale structure. By representing the tensor as a sum of compressed tensors defined on increasingly coarse grids, the format captures low-rank …

    mit Repository record for Themes in numerical tensor calculus (opens in a new tab)

  10. Tensors and Stochastic Automata Networks with Application to Chemical Kinetics

    … simulations to more sophisticated higher-order tensors and stochastic automata networks. Many revolve around solving the chemical master equation that arises in the modeling of the underlying biochemical kinetics. Traditionally, the chemical master equation models states consisting of the …

    alabama Repository record for Tensors and Stochastic Automata Networks with Application to Chemical Kinetics (opens in a new tab)

  11. Algorithms and software for efficient tensor decompositions

    Tensors, which generalize vectors and matrices to higher dimensions, provide a powerful framework for representing and analyzing multi-way data arising in science and engineering. Their ability to capture complex, multi-relational structures makes them invaluable in applications ranging from …

    uiuc Repository record for Algorithms and software for efficient tensor decompositions (opens in a new tab)