Search Results for author: Zachary Manchester

Found 8 papers, 7 papers with code

Joint inference and input optimization in equilibrium networks

1 code implementation NeurIPS 2021 Swaminathan Gurumurthy, Shaojie Bai, Zachary Manchester, J. Zico Kolter

Many tasks in deep learning involve optimizing over the \emph{inputs} to a network to minimize or maximize some objective; examples include optimization over latent spaces in a generative model to match a target image, or adversarially perturbing an input to worsen classifier performance.

Denoising Meta-Learning

Training Structured Mechanical Models by Minimizing Discrete Euler-Lagrange Residual

1 code implementation5 May 2021 Kunal Menda, Jayesh K. Gupta, Zachary Manchester, Mykel J. Kochenderfer

Structured Mechanical Models (SMMs) are a data-efficient black-box parameterization of mechanical systems, typically fit to data by minimizing the error between predicted and observed accelerations or next states.

Decision Making Time Series

Structured Mechanical Models for Robot Learning and Control

1 code implementation L4DC 2020 Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer

Deep neural networks have been used to learn models of robot dynamics from data, but they suffer from data-inefficiency and the difficulty to incorporate prior knowledge.

Linear-Time Variational Integrators in Maximal Coordinates

2 code implementations26 Feb 2020 Jan Brüdigam, Zachary Manchester

Most dynamic simulation tools parameterize the configuration of multi-body robotic systems using minimal coordinates, also called generalized or joint coordinates.

Robotics Computational Physics

ALGAMES: A Fast Solver for Constrained Dynamic Games

1 code implementation22 Oct 2019 Simon Le Cleac'h, Mac Schwager, Zachary Manchester

We evaluate our solver in the context of autonomous driving on scenarios with a strong level of interactions between the vehicles.

Autonomous Driving

Non-linear System Identification from Partial Observations via Iterative Smoothing and Learning

no code implementations25 Sep 2019 Kunal Menda, Jean de Becdelièvre, Jayesh K Gupta, Ilan Kroo, Mykel J. Kochenderfer, Zachary Manchester

System identification is the process of building a mathematical model of an unknown system from measurements of its inputs and outputs.

A General Framework for Structured Learning of Mechanical Systems

1 code implementation22 Feb 2019 Jayesh K. Gupta, Kunal Menda, Zachary Manchester, Mykel J. Kochenderfer

We address the need for a flexible, gray-box model of mechanical systems that can seamlessly incorporate prior knowledge where it is available, and train expressive function approximators where it is not.

Model-based Reinforcement Learning

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