JumpBackHash: Say Goodbye to the Modulo Operation to Distribute Keys Uniformly to Buckets

Constrained deep learning is an advanced approach to training deep neural networks by incorporating domain-specific constraints into the learning process.

IBM AI explainability

Evaluate ranked-choice elections in a notebook interface. Able to import a wide-range of elections and detect non-monotonic results.

Experiments of the ACL 2021 Findings paper "Language Models Use Monotonicity to Assess NPI Licensing"

Research on integrating datalog & lambda calculus via monotonicity types

R package: monotonicity

Code of "Not Too Close and Not Too Far: Enforcing Monotonicity Requires Penalizing The Right Points"

A library for quickchecking lattice modules and associated operations

Universal Dependency polarization for monotonicity based natural language inference

This repository contains my seminar work (literature review) for topics in Machine Learning, Pattern Recognition at Paderborn University. Each topic is in a separate folder and the folder name is the topic of my seminar work.

Quantifiers and monotonicity in reasoning tasks

Techniques for data mining.

Summaries and annotations of research papers across broad spectrum of AI and ML.

This repository contains the code to reproduce all of the results in our paper: Making Learners (More) Monotone, T J Viering, A Mey, M Loog, IDA 2020.

A simple program demonstrating O(n*log(n)) search on a monotonic matrix, versus the O(n**2) search required for a non-monotonic matrix.

General Constraint Regression Models

Implements an AutoIncrement counter class similar to PostgreSQL's sequence.