31 citations · 84 across the 12 of their papers we have counts for
4 papers · 1 filter
Solving Inverse Problems via Diffusion Optimal Control
Henry Li, Marcus Pereira
Existing approaches to diffusion-based inverse problem solvers frame the signal recovery task as a probabilistic sampling episode, where the solution is drawn from the desired post…
NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-End Learning and Control
Ioannis Exarchos, Marcus A. Pereira, Ziyi Wang +1
In this work we propose the use of adaptive stochastic search as a building block for general, non-convex optimization operations within deep neural network architectures. Specific…
Deep 2FBSDEs For Systems With Control Multiplicative Noise
Marcus A Pereira, Ziyi Wang, Tianrong Chen +2
We present a deep recurrent neural network architecture to solve a class of stochastic optimal control problems described by fully nonlinear Hamilton Jacobi Bellmanpartial differen…
MPC-Inspired Neural Network Policies for Sequential Decision Making
Marcus Pereira, David D. Fan, Gabriel Nakajima An +1
In this paper we investigate the use of MPC-inspired neural network policies for sequential decision making. We introduce an extension to the DAgger algorithm for training such pol…