cgartrel / nonsymmetric-dpp-learning

PyTorch implementation of nonsymmetric determinantal point process (DPP) learning.

Nonsymmetric DPP Learning

PyTorch implementation of nonsymmetric determinantal point process (DPP) learning. For details, see our Learning Nonsymmetric Determinantal Point Processes paper (NeurIPS 2019 poster).

Installation

Install required Python packages:

$ pip install --user --requirement requirements.txt

Usage

Train and evaluate a nonsymmetric DPP model using the Amazon apparel baby registry dataset:

$ cd src
$ python main.py --dataset_name basket_ids --input_file data/1_100_100_100_apparel_regs.csv --num_sym_embedding_dims 30 --num_nonsym_embedding_dims 30

For a full list of command-line options:

$ python main.py --help

nonsymmetric-dpp-learning's Issues

The code of Deep Determinantal Point Processes

hello there, thanks for sharing the code, i'm also interested in your published paper "Deep Determinantal Point Processes” and you said in the paper the code will be made publicly, could you please share the code? Much appreciated!

Outputting the kernel matrix

thanks for the code! Is there a simple way to output the learned kernel? I'm especially interested in outputting learned asymmetric kernels.