Jul 19, 2022 · We present Theseus, an efficient application-agnostic open source library for differentiable nonlinear least squares (DNLS) optimization built on PyTorch.
Theseus is an efficient application-agnostic library for building custom nonlinear optimization layers in PyTorch to support constructing various problems in ...
Theseus is an efficient application-agnostic library for building custom nonlinear optimization layers in PyTorch to support constructing various problems ...
In Theseus, we imple- ment sparse linear solvers that are differentiable end-to-end and make them efficient with custom. CPU and CUDA backends to support ...
Oct 31, 2022 · We present Theseus, an efficient application-agnostic open source library for differentiable nonlinear least squares (DNLS) optimization built on PyTorch.
We present Theseus, an efficient application-agnostic open source library for differentiable nonlinear least squares (DNLS) optimization built on PyTorch, ...
As part of Theseus, we include differentiable versions of cost functions like smoothness and collision in [5], and an example of how to setup end-to-end.
We present Theseus, an efficient application-agnostic open source library for differentiable nonlinear least squares (DNLS) optimization built on PyTorch, ...
Apr 3, 2024 · We present Theseus, an efficient application-agnostic open source library for differentiable nonlinear least squares (DNLS) optimization ...
We present Theseus, an efficient application-agnostic open source library for differentiable nonlinear least squares (DNLS) optimization built on PyTorch.