10 Repositories
Latest Python Libraries
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.
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
reXmeX is recommender system evaluation metric library.
A general purpose recommender metrics library for fair evaluation.
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
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
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
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
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.)
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
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