PyTorch + HuggingFace code for RetoMaton: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022), including an implementation of kNN-LM and kNN-MT
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Updated
Oct 20, 2022 - Python
PyTorch + HuggingFace code for RetoMaton: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022), including an implementation of kNN-LM and kNN-MT
A python library with implementations of 15 classical heuristics for the capacitated vehicle routing problem.
✌️ 👌 ✊ 📷 Sign Language Recognition using Python
PyTorch code for the RetoMaton paper: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022)
SIGIR 2017: Embedding-based query expansion for weighted sequential dependence retrieval model
The fastest Quadtree for Python. Just pip install and go. Quick inserts, easy neighbor queries, and seamless Pygame support.
Official implementation for [N2DCX] Nearest Neighborhood-Based Deep Clustering for Source Data-absent Unsupervised Domain Adaptation
Robustness for Non-Parametric Classification: A Generic Attack and Defense
Differentiating between Twitter bots and real users
Python code for visualizations of algorithms that provide approximate solutions to TSP along with two lower bound approximations
Optimizing vehicle routing for efficient delivery of goods to various customer locations while minimizing costs. This project implements algorithms to solve the Capacitated Vehicle Routing Problem (CVRP) using Python and frameworks like Google OR-Tools and the nearest neighbor heuristic, with the latter being used for comparison purposes.
Client interface for requesting hardware accelerated distance calculation
A Travelling Salesman Problem (TSP) solver using a hybrid of strategies
Integrating NNK evaluation with VISSL framework
A Python package for visualizing graph algorithms.
query server for approximate nearest neighbors
🔬🥇🧠🍔 Automated Gold Particle Analysis For Freeze Fracture Replica Electron Microscopy Images
Using Python Sign Recognition
Three different basic data analysis processes of biomedical data for Python. Level: beginner (~200 lines of pure code).
Heuristics and metaheuristics for enhancing Run-Length Encoding in a database
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