LT-OCF

LT-OCF: Learnable-Time ODE-based Collaborative Filtering, CIKM'21

Our proposed LT-OCF

lt-ocf

Our proposed dual co-evolving ODE

dualres

Setup Python environment for LT-OCF

Install python environment

conda env create -f environment.yml

Activate environment

conda activate lt-ocf

Reproducibility

Usage

In terminal

  • Run the shell file (at the root of the project)
# run lt-ocf (gowalla dataset, rk4 solver, learnable time)
sh ltocf_gowalla_rk4.sh

# run lt-ocf (gowalla dataset, rk4 solver, fixed time)
sh ltocf_gowalla_rk4_fixed.sh

Arguments (see more arguments in parse.py)

  • gpuid
    • default: 0
  • dataset
    • gowalla, yelp2018, amazon-book
  • model
    • ltocf
  • solver
    • euler, rk4, implicit_adams, dopri5
  • adjoint
    • False, True
  • K
    • 1, 2, 3, 4
  • learnable_time
    • True, False
  • dual_res
    • False, True

GitHub

https://github.com/jeongwhanchoi/LT-OCF