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Stanford
- Palo Alto, CA
- https://lillianpetersen.github.io
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GRU-variable-length-inputs
GRU-variable-length-inputs PublicFunctions for training a GRU (gated recurrent unit) that can work with variable length inputs. Hyperparameters are tuned via optuna, and the hyperparameter search is parallelized over multiple GPUs.
Python
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parallel-hyperparameter-tuning
parallel-hyperparameter-tuning PublicCode for tuning hyperparameters using optuna across multiple GPUs within one node
Python
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easy-clustering
easy-clustering PublicDetermine how many clusters should exist in your dataset via hierarchical clustering and plot the clusters on a UMAP
Python
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