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## Reason
It is often cumbersome and difficult to derive the gradient for PDE-constrained inverse optimization. It involves developing an adjoint of the forward problem and derivatives with respect…
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Since EI has an analytical formula, argmax(EI) should easily incorporate constraints. An example is weights, where sum(x's)=1, or points in a circle, where x^2+y^2
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A few keywords include,
- Multi-Threaded sensor fusion
- Maximum A Posterior Inference using non-linear optimization through GTSAM iSAM2 solver
- Pre-integrated IMU factors
- Pre-integrated Legged…
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# Semester-VI (Practice and Homework Assignments)
>
> **EE1370 (Data Analytics)**
> - Transfromations of random variables
Transformations
> **CS5040(Linear Optimization)**
> - Smplex algori…
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@rgrente here is a trial I made, this is not completely out of the picture, it's quite linear as you were saying. I don't (yet) interpolate Gribs data.
Comment on the track:
1. lots of tacking
2. u…
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## ❓ Questions and Help
Hi theseus team,
I'm currently using theseus to solve some non-linear optimization problem. In my case, some cost function will return negative cost. However, in the object…
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## 🚀 Feature
The option for constraint-aware optimization techniques within torch.optim. [Sequential Quadratic Programming](https://en.wikipedia.org/wiki/Sequential_quadratic_programming) is a very c…
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This is a great project, Open source training from scratch, simple and easy to use, especially suitable for ordinary people.
The currently sota algorithm models are highly similar to llama3. I hope…
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**Conference** :
**Link** : http://arxiv.org/abs/2102.06810
**Authors' Affiliation** : Facebook AI Research
**TL;DR** : SimSiam 논문의 원인을 탐구하는 논문. "How can SSL with only positive pairs avoid represe…
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I ran into an example with some badly scaled variables (Cameron Trivedi count data similar to randhi).
It took me a while to figure out that the bad scaling was the reason for numerical problems:
- v…