The safety filter: A unified view of safety-critical control in autonomous systems
Recent years have seen significant progress in the realm of robot autonomy, accompanied
by the expanding reach of robotic technologies. However, the emergence of new …
by the expanding reach of robotic technologies. However, the emergence of new …
Level set methods and dynamic implicit surfaces
This book is intended primarily as a textbook for second-year undergraduate students in
mathematics, mathematical physics, and engineering. The book is designed as a first …
mathematics, mathematical physics, and engineering. The book is designed as a first …
Implicit geometric regularization for learning shapes
Representing shapes as level sets of neural networks has been recently proved to be useful
for different shape analysis and reconstruction tasks. So far, such representations were …
for different shape analysis and reconstruction tasks. So far, such representations were …
Pose-ndf: Modeling human pose manifolds with neural distance fields
We present Pose-NDF, a continuous model for plausible human poses based on neural
distance fields (NDFs). Pose or motion priors are important for generating realistic new …
distance fields (NDFs). Pose or motion priors are important for generating realistic new …
Iron: Inverse rendering by optimizing neural sdfs and materials from photometric images
We propose a neural inverse rendering pipeline called IRON that operates on photometric
images and outputs high-quality 3D content in the format of triangle meshes and material …
images and outputs high-quality 3D content in the format of triangle meshes and material …
[图书][B] Variational analysis and applications
BS Mordukhovich - 2018 - Springer
Boris S. Mordukhovich Page 1 Springer Monographs in Mathematics Boris S. Mordukhovich
Variational Analysis and Applications Page 2 Springer Monographs in Mathematics Editors-in-Chief …
Variational Analysis and Applications Page 2 Springer Monographs in Mathematics Editors-in-Chief …
Limitations of physics informed machine learning for nonlinear two-phase transport in porous media
O Fuks, HA Tchelepi - … of Machine Learning for Modeling and …, 2020 - dl.begellhouse.com
Deep learning techniques have recently been applied to a wide range of computational
physics problems. In this paper, we focus on developing a physics-based approach that …
physics problems. In this paper, we focus on developing a physics-based approach that …
[图书][B] Mathematical control theory for stochastic partial differential equations
Q Lü, X Zhang - 2021 - Springer
It is well-known that Control Theory was founded by N. Wiener in 1948 ([349]). After that, this
theory was greatly extended to various complicated setting and widely used in sciences and …
theory was greatly extended to various complicated setting and widely used in sciences and …
[图书][B] A proof that artificial neural networks overcome the curse of dimensionality in the numerical approximation of Black–Scholes partial differential equations
Artificial neural networks (ANNs) have very successfully been used in numerical simulations
for a series of computational problems ranging from image classification/image recognition …
for a series of computational problems ranging from image classification/image recognition …
Income and wealth distribution in macroeconomics: A continuous-time approach
Abstract We recast the Aiyagari–Bewley–Huggett model of income and wealth distribution in
continuous time. This workhorse model—as well as heterogeneous agent models more …
continuous time. This workhorse model—as well as heterogeneous agent models more …