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**Submitting author:** @umutcanaltin (Umut Can Altin)
**Repository:** https://github.com/umutcanaltin/fpgai_compiler
**Branch with paper.md** (empty if default branch): main
**Version:** v1.0.0
**Edit…
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- [x] make reset faster by having a pid bring the motor to a stop. then maybe have a second one stop the pendulum from oscillating faster
- also maybe make the angle threshold a bit wider for the p…
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Hello! I was trying to use the code in the "experiment_dblpend" directory. As long as it is training the neural network with the loss "baseline_nn", everything is fine.
The moment I try to use the …
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Hi, very interesting work and nice presentation in paper. I'm interested in applying conditional flow matching to the tasks without paired training data. For example, many image restoration tasks do n…
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What do we want out of our experiments? In the setting of offline RL, we want our algorithm to
1. Achieve reasonable success on the task
2. Show that adding distribution risk improves over vanilla …
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Out of two command/sensor parameters, we only perform closed-loop control on one of them (https://github.com/HUMASoft/yarp-devices/issues/3): the polar angle (*inclinación*). Attemps on replicating th…
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Hi, thanks a lot for developing the package, I am just exploring the packages and see how it can be used to analyze some EEG signals.
I tried to compare the `nk.entropy_multiscale` and `nk_entropy…
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### Objective
The goal of this issue is to implement a Graph Convolutional Neural Network (GCNs-Net) model for decoding time-resolved EEG motor imagery signals, as outlined in the paper "[GCNs-Net: A…
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During Manny's, Erika's, and my presentation we talked about further graph theoretic techniques that could be applied to a dynamic graph of neural cell assemblies. One avenue I found is something call…
whock updated
9 years ago
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* [Link](https://arxiv.org/abs/1907.04490)
* Title: Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning
* Keywords (optional):
* Authors (optional):
* Reason (optional)…