Search Results for author: Daniel Pfrommer

Found 4 papers, 2 papers with code

The Power of Learned Locally Linear Models for Nonlinear Policy Optimization

no code implementations16 May 2023 Daniel Pfrommer, Max Simchowitz, Tyler Westenbroek, Nikolai Matni, Stephen Tu

A common pipeline in learning-based control is to iteratively estimate a model of system dynamics, and apply a trajectory optimization algorithm - e. g.~$\mathtt{iLQR}$ - on the learned model to minimize a target cost.

TaSIL: Taylor Series Imitation Learning

1 code implementation30 May 2022 Daniel Pfrommer, Thomas T. C. K. Zhang, Stephen Tu, Nikolai Matni

We propose Taylor Series Imitation Learning (TaSIL), a simple augmentation to standard behavior cloning losses in the context of continuous control.

Continuous Control Imitation Learning

Linear Variational State-Space Filtering

1 code implementation4 Jan 2022 Daniel Pfrommer, Nikolai Matni

We introduce Variational State-Space Filters (VSSF), a new method for unsupervised learning, identification, and filtering of latent Markov state space models from raw pixels.

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