56 Repositories
Python ranking Libraries
Code for our SIGIR 2022 accepted paper : P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-based Learning and Pre-finetuning
P3 Ranker Implementation for our SIGIR2022 accepted paper: P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-bas
LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EGRerank, Seq2Slate.
LibRerank LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EGRer
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model About This repository contains the code to replicate the syn
SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking
SPLADE 🍴 + 🥄 = 🔎 This repository contains the weights for four models as well as the code for running inference for our two papers: [v1]: SPLADE: S
Python implementation of Weng-Lin Bayesian ranking, a better, license-free alternative to TrueSkill
Python implementation of Weng-Lin Bayesian ranking, a better, license-free alternative to TrueSkill This is a port of the amazing openskill.js package
No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consistency
This repository contains the implementation for the paper: No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consiste
Maiden & Spell community player ranking based on tournament data.
MnSRank Maiden & Spell community player ranking based on tournament data. Why? 2021 just ended and this seemed like a cool idea. Elo doesn't work well
Fast Learning of MNL Model From General Partial Rankings with Application to Network Formation Modeling
Fast-Partial-Ranking-MNL This repo provides a PyTorch implementation for the CopulaGNN models as described in the following paper: Fast Learning of MN
PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability
PCACE: A Statistical Approach to Ranking Neurons for CNN Interpretability PCACE is a new algorithm for ranking neurons in a CNN architecture in order
Establishing Strong Baselines for TripClick Health Retrieval; ECIR 2022
TripClick Baselines with Improved Training Data Welcome 🙌 to the hub-repo of our paper: Establishing Strong Baselines for TripClick Health Retrieval
nfelo: a power ranking, prediction, and betting model for the NFL
nfelo nfelo is a power ranking, prediction, and betting model for the NFL. Nfelo take's 538's Elo framework and further adapts it for the NFL, hence t
AI-based, context-driven network device ranking
Batea A batea is a large shallow pan of wood or iron traditionally used by gold prospectors for washing sand and gravel to recover gold nuggets. Batea
Python client and module for BGP Ranking
Python client and module for BGP Ranking THis project will make querying BGP Ranking easier. Installation pip install pybgpranking Usage Command line
DeepDiffusion: Unsupervised Learning of Retrieval-adapted Representations via Diffusion-based Ranking on Latent Feature Manifold
DeepDiffusion Introduction This repository provides the code of the DeepDiffusion algorithm for unsupervised learning of retrieval-adapted representat
codes for Self-paced Deep Regression Forests with Consideration on Ranking Fairness
Self-paced Deep Regression Forests with Consideration on Ranking Fairness This is official codes for paper Self-paced Deep Regression Forests with Con
Official Implementation for the paper DeepFace-EMD: Re-ranking Using Patch-wise Earth Mover’s Distance Improves Out-Of-Distribution Face Identification
DeepFace-EMD: Re-ranking Using Patch-wise Earth Mover’s Distance Improves Out-Of-Distribution Face Identification Official Implementation for the pape
The repo for reproducing Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study
ECIR Reproducibility Paper: Seed-driven Document Ranking for Systematic Reviews: A Reproducibility Study This code corresponds to the reproducibility
DaReCzech is a dataset for text relevance ranking in Czech
Dataset DaReCzech is a dataset for text relevance ranking in Czech. The dataset consists of more than 1.6M annotated query-documents pairs,
Multi-Task Deep Neural Networks for Natural Language Understanding
New Release We released Adversarial training for both LM pre-training/finetuning and f-divergence. Large-scale Adversarial training for LMs: ALUM code
IBD Style Relative Strength Percentile Ranking of Stocks (i.e. 0-100 Score).
relative-strength IBD Style Relative Strength Percentile Ranking of Stocks (i.e. 0-100 Score). I also made a TradingView indicator, but it cannot give
Unsupervised Feature Ranking via Attribute Networks.
FRANe Unsupervised Feature Ranking via Attribute Networks (FRANe) converts a dataset into a network (graph) with nodes that correspond to the features
(NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductive few-shot classification"
SSR (NeurIPS 2021) Pytorch implementation of paper "Re-ranking for image retrieval and transductivefew-shot classification" [Paper] [Project webpage]
Self-Supervised Document-to-Document Similarity Ranking via Contextualized Language Models and Hierarchical Inference
Self-Supervised Document Similarity Ranking (SDR) via Contextualized Language Models and Hierarchical Inference This repo is the implementation for SD
Confident Semantic Ranking Loss for Part Parsing
Confident Semantic Ranking Loss for Part Parsing
reXmeX is recommender system evaluation metric library.
A general purpose recommender metrics library for fair evaluation.
Cardano SundaeSwap ISO SPO vote ranking script
Cardano SundaeSwap ISO SPOs vote ranking This Python 3 script uses the database populated by cardano-db-sync from the Cardano blockchain to generate a
PECOS - Prediction for Enormous and Correlated Spaces
PECOS - Predictions for Enormous and Correlated Output Spaces PECOS is a versatile and modular machine learning (ML) framework for fast learning and i
For when you really need to rank things
Comparisonator For when you really need to rank things. Do you know that feeling when there's this urge deep within you that tells you to compare thin
Official implementation of NeurIPS 2021 paper "Contextual Similarity Aggregation with Self-attention for Visual Re-ranking"
CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We
Official implementation of NeurIPS 2021 paper "Contextual Similarity Aggregation with Self-attention for Visual Re-ranking"
CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We
[2021 MultiMedia] CONQUER: Contextual Query-aware Ranking for Video Corpus Moment Retrieval
CONQUER: Contexutal Query-aware Ranking for Video Corpus Moment Retreival PyTorch implementation of CONQUER: Contexutal Query-aware Ranking for Video
RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering
RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering Authors: Xi Ye, Semih Yavuz, Kazuma Hashimoto, Yingbo Zhou and
NLPIR tutorial: pretrain for IR. pre-train on raw textual corpus, fine-tune on MS MARCO Document Ranking
pretrain4ir_tutorial NLPIR tutorial: pretrain for IR. pre-train on raw textual corpus, fine-tune on MS MARCO Document Ranking 用作NLPIR实验室, Pre-training
A multilingual version of MS MARCO passage ranking dataset
mMARCO A multilingual version of MS MARCO passage ranking dataset This repository presents a neural machine translation-based method for translating t
Ranking Models in Unlabeled New Environments (iccv21)
Ranking Models in Unlabeled New Environments Prerequisites This code uses the following libraries Python 3.7 NumPy PyTorch 1.7.0 + torchivision 0.8.1
FastReID is a research platform that implements state-of-the-art re-identification algorithms.
FastReID is a research platform that implements state-of-the-art re-identification algorithms.
A tiny, friendly, strong baseline code for Person-reID (based on pytorch).
Pytorch ReID Strong, Small, Friendly A tiny, friendly, strong baseline code for Person-reID (based on pytorch). Strong. It is consistent with the new
TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform
TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform
Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness
Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness This repository contains the code used for the exper
Code and data of the ACL 2021 paper: Few-Shot Text Ranking with Meta Adapted Synthetic Weak Supervision
MetaAdaptRank This repository provides the implementation of meta-learning to reweight synthetic weak supervision data described in the paper Few-Shot
A curated list of awesome resources related to Semantic Search🔎 and Semantic Similarity tasks.
A curated list of awesome resources related to Semantic Search🔎 and Semantic Similarity tasks.
Fast, differentiable sorting and ranking in PyTorch
Torchsort Fast, differentiable sorting and ranking in PyTorch. Pure PyTorch implementation of Fast Differentiable Sorting and Ranking (Blondel et al.)
MILES is a multilingual text simplifier inspired by LSBert - A BERT-based lexical simplification approach proposed in 2018. Unlike LSBert, MILES uses the bert-base-multilingual-uncased model, as well as simple language-agnostic approaches to complex word identification (CWI) and candidate ranking.
MILES Multilingual Lexical Simplifier Explore the docs » Read LSBert Paper · Report Bug · Request Feature About The Project MILES is a multilingual te
ReConsider is a re-ranking model that re-ranks the top-K (passage, answer-span) predictions of an Open-Domain QA Model like DPR (Karpukhin et al., 2020).
ReConsider ReConsider is a re-ranking model that re-ranks the top-K (passage, answer-span) predictions of an Open-Domain QA Model like DPR (Karpukhin
An official implementation for "CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval"
The implementation of paper CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval. CLIP4Clip is a video-text retrieval model based
Large-scale linear classification, regression and ranking in Python
lightning lightning is a library for large-scale linear classification, regression and ranking in Python. Highlights: follows the scikit-learn API con
An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow implementation of SERank model. The code is developed based on TF-Ranking.
SERank An efficient and effective learning to rank algorithm by mining information across ranking candidates. This repository contains the tensorflow
This repository provides train&test code, dataset, det.&rec. annotation, evaluation script, annotation tool, and ranking.
SCUT-CTW1500 Datasets We have updated annotations for both train and test set. Train: 1000 images [images][annos] Additional point annotation for each
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Learning embeddings for classification, retrieval and ranking.
StarSpace StarSpace is a general-purpose neural model for efficient learning of entity embeddings for solving a wide variety of problems: Learning wor
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Best Practices on Recommendation Systems
Recommenders What's New (February 4, 2021) We have a new relase Recommenders 2021.2! It comes with lots of bug fixes, optimizations and 3 new algorith
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree