Python Importance-reweighting Resources

MoEBERT This PyTorch package implements MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation (NAACL 2022). Installation Create an

Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python 📊

CIFS This repository provides codes for CIFS (ICML 2021). CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Sel

pypmc pypmc is a python package focusing on adaptive importance sampling. It can be used for integration and sampling from a user-defined target densi

IrwGAN (ICCV2021) Unaligned Image-to-Image Translation by Learning to Reweight [Update] 12/15/2021 All dataset are released, trained models and genera

Differentiable Annealed Importance Sampling (DAIS) This repository contains the code to reproduce the DAIS results from the paper Differentiable Annea

Meta-Weight-Net NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Official Pytorch implementation for noisy labels). The

Adversarial Reweighting for Partial Domain Adaptation Code for paper "Xiang Gu, Xi Yu, Yan Yang, Jian Sun, Zongben Xu, Adversarial Reweighting for Par

Robust Self-augmentation for NER with Meta-reweighting

LOFO (Leave One Feature Out) Importance calculates the importances of a set of features based on a metric of choice, for a model of choice, by iteratively removing each feature from the set, and evaluating the performance of the model, with a validation scheme of choice, based on the chosen metric.

XAI - An eXplainability toolbox for machine learning XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contai

Reproducibility materials for "Importance of Kernel Bandwidth in Quantum Machine Learning" Repo structure: code contains Python scripts used to genera

Feature Importance-aware Attack(FIA) This repository contains the code for the paper: Feature Importance-aware Transferable Adversarial Attacks (ICCV

Instance-wise Feature Importance in Time (FIT) FIT is a framework for explaining time series perdiction models, by assigning feature importance to eve

From global to local MDI variable importances for random forests and when they are Shapley values Antonio Sutera ([email protected]) Gilles Lou

SimplEx - Explaining Latent Representations with a Corpus of Examples Code Author: Jonathan Crabbé ([email protected]) This repository contains the imp

source code for NeurIPS21 paper robabilistic Margins for Instance Reweighting in Adversarial Training

Hierarchical neural-net interpretations (ACD) 🧠 Produces hierarchical interpretations for a single prediction made by a pytorch neural network. Offic

Fast MST Algorithm Implementation of fast algorithms for (Maximum Spanning Tree) MST parsing that includes fast ArcMax+Reweighting+Tarjan algorithm fo

An NCE implementation in pytorch About NCE Noise Contrastive Estimation (NCE) is an approximation method that is used to work around the huge computat

I-SECRET This is the implementation of the MICCAI 2021 Paper "I-SECRET: Importance-guided fundus image enhancement via semi-supervised contrastive con

SYMPAIS: Symbolic Parallel Adaptive Importance Sampling for Probabilistic Program Analysis Overview | Installation | Documentation | Examples | Notebo

Image Crop Analysis This is a repo for the code used for reproducing our Image Crop Analysis paper as shared on our blog post. If you plan to use this

RIIT Our open-source code for RIIT: Rethinking the Importance of Implementation Tricks in Multi-AgentReinforcement Learning. We implement and standard

MARL Tricks Our codes for RIIT: Rethinking the Importance of Implementation Tricks in Multi-AgentReinforcement Learning. We implemented and standardiz

Despite its importance, there are few previous works applying I2I translation to webtoon. I collected dataset from naver webtoon 연애혁명 and tried to transfer human faces to webtoon domain.