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### Integration Layer Plan for NSCR Framework
The NSCR (Neuro-Symbolic Cognitive Reasoning) framework involves integrating the SymbolicReasoningEngine with a neural network engine and an integratio…
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Hi,
is there an example for train / retrain / fine tune a network created with the "Neural Network Console" ?
I tryed with the result.nnp net.nntxt and model.nnp, but i didn't find the right way.
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Papers:
- Same, Same But Different - Recovering Neural Network Quantization Error Through Weight Factorization https://arxiv.org/abs/1902.01917
- Up or Down? Adaptive Rounding for Post-Training …
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On GPU hardware, in production scripts, post-processing takes twice as long as neural network inference.
On an NVidia GeForce GTX 1080 Ti (12GB RAM), for one full-size Sentinel-2 tile, CRGA OS2 UNe…
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if we get a sparse model, is there an effective way to do sparse convolutional for inference? I just know 2015 CVPR paper "Sparse Convolutional Neural Networks", is there exit another more effective…
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### Start with the `why`:
To run inference on both mono frames.
### Move to the `what`:
Ability to run a neural network on both left&right mono frames instead of on the color frame (by default). …
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Hi!
Are there plans for making a low precision inference mode like many other neural network frameworks out there?
Would be really helpful for embedded applications where we have very limited memory…
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Mobile Neural Network (MNN), a universal and efficient inference engine tailored to mobile applications. In this paper, the contributions of MNN include:
1. presenting a mechanism called pre-infer…
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Currently, if the choice of device is ambiguous, we run an [out-of-band dialogue to let the user choose](https://github.com/stanford-oval/genie-toolkit/blob/master/lib/dialogue-agent/execution_dialogu…