https://github.com/GPflow/GPflow
Revision f9ffcac830b10904cf610cb7a1e67d2564ec352e authored by John Bradshaw on 26 September 2017, 09:32:39 UTC, committed by John Bradshaw on 26 September 2017, 09:32:39 UTC
* random features for GPR model (untested) * small script demonstrating how it works * kernels back to numpy randomness as more controllable.
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- f9ffcac830b10904cf610cb7a1e67d2564ec352e
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Tip revision: f9ffcac830b10904cf610cb7a1e67d2564ec352e authored by John Bradshaw on 26 September 2017, 09:32:39 UTC
Putting random features into GPR model
Putting random features into GPR model
Tip revision: f9ffcac
roadmap.md
This document covers major planned development items for GPflow.
# Computational speed
- Add further benchmarks to [benchmark repository](https://github.com/GPflow/GPflowBenchmarks) including multiple GPUs.
- Incorporate remaining Tom Nickson GPU code from [branch](https://github.com/c0g/tomserflow) into TensorFlow main.
# Features
- Add ability to exploit Kronecker structure.
# Housekeeping
- See also issues marked "enhancement" in the GitHub [list](https://github.com/GPflow/GPflow/issues).
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