-
-
Hi, I'm using Ipopt with MathOptInterface to solve trajectory optimization problems. When I was providing hessians for the objective function with only diagonal elements, everything worked fine. Howev…
-
### Summary
It seems to me that `revert` and external `cache`s can be completely avoided by using the usual `fit` and `predict` approach for machine learning pipelines. And this can be done in a fu…
-
**Submitting author:** @victoraalves (Victor Alves)
**Repository:** https://github.com/CODES-group/opyrability
**Branch with paper.md** (empty if default branch):
**Version:** v1.4.3
**Editor:** @kyl…
-
**Submitting author:** @axtimhaus (Max Weiner)
**Repository:** https://github.com/pyroll-project/pyroll-core
**Branch with paper.md** (empty if default branch): joss
**Version:** 2.1
**Editor:** @phil…
-
## Idea 💡
The **ULTIMATE** achievement for this project would be if Auto-GPT was able to recursively improve itself. That, after-all, is how AGI is predicted by many to come about.
## Suggestion …
-
### Question
I'm running a2c with default parameters on BreakoutNoFrameskip-v4, with two different training scenario, where the only difference is that one uses `n_envs=16` (orange) while the other o…
-
Many of us have the overwhelming sense that the newer versions of SNOPT perform worse on the problem instances that we have in Drake. I've discussed with other colleagues in the community who agree (n…
-
**Title:** Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training
**Abstract:** Given the massive cost of language model pre-training, a non-trivial improvement of the…
-
In an earlier version (maybe a 2020 release) of tesseract and trajopt, a trajectory optimization problem can be constructed by such a workflow (part of my code):
```
// create the problem constr…