# pmlayer

**Repository Path**: mirrors_ibm/pmlayer

## Basic Information

- **Project Name**: pmlayer
- **Description**: Neural network layer to handle monotonicity constraints.
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-10-24
- **Last Updated**: 2026-07-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Partially Monotone Layer

Partially monotome layer (`pmlayer`) is a library for neural network models.
It provides several neural network layers to add monotonicity constraints on neural network models.
Current implementation is available only for PyTorch.

Read the [documentation](https://ibm.github.io/pmlayer/) to get started, and feel free to contact us for any inquiry.

# Installation

You can install `pmlayer` by using the `pip` command:

```pip install pmlayer```


# Citation

Please consider citing this paper.
> H. Yanagisawa, K. Miyaguchi, and T. Katsuki, "Hierarchical Lattice Layer for Partially Monotone Regression," NeurIPS 2022.