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Describe data for clarity and sharing
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Train a separate model specifically for the task of inverse modeling, where the goal is to infer the previous state and rule from a given state or sequence of states. This model would essentially lear…
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MuZero: https://arxiv.org/abs/1911.08265
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Implement Automated Logic to Identify and Mitigate Deep Double Descent Phenomenon
### Feature Request
#### Summary:
I propose the addition of an automated mechanism within the framework that de…
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Want to simulate a GoT style story with tons of characters with complex relationships.
The plan:
- Generate families with power, alliances, rivalry
- Generate characters within families
- Have charac…
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## Brief
TODO: mention auto experiment setting
With AutoTrain, we hope to solve the problem of autonomous neural network optimization by teaching an agent to recognise a relationship between _…
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TensorFlow Graphics was [first released](https://blog.tensorflow.org/2019/05/introducing-tensorflow-graphics_9.html) at Google I/O in 2019, and since, the library grew a lot, both in terms of core com…
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I am working on creating a Neural Model Predictive Controller (MPC) using `csnlp.wrappers.mpc` within the `csnlp` library. My trained PyTorch LSTM model is converted into a CasADi function using `l4ca…
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- [ ] Talk about the complexity of the algorithm running tim used.
- [x] Web characterization **[6]**
- [x] Methods for sampling, Web dynamics, Estimating freshness and age, Characterization of We…
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Hi, team!
I'm interested in it but it's hard to get it.
I have some questions about wide networks.
1) What's the prediction of wide networks, e.g., NNGP? Evaluated mean of GP? Is it deterministic? If …