Stars
Streamlit LLM app examples for getting started
A list of selected resources, methods, and tools dedicated to Legal Text Analytics.
Code for Everything Has a Cause: Leveraging Causal Inference in Legal Text Analysis (NAACL 2021 oral paper)
Silero Models: pre-trained text-to-speech models made embarrassingly simple
Keras implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation". Includes synthetic GED data.
State-of-the-Art Embeddings, Retrieval, and Reranking
TensorFlow code and pre-trained models for BERT
Graph convolutional networks (GCN), graphSAGE and graph attention networks (GAT) for text classification
Create a knowledge graph out of unstructed legal text - use said knowledge graph in a graph augmented retrieval augmented generation pipeline
Source code and dataset for the CCKS2021 paper "Text-guided Legal Knowledge Graph Reasoning".
Benchmarking Legal Knowledge of Large Language Models
Time series anomaly detection algorithm implementations for TimeEval (Docker-based)
Source code of CIKM'22 paper: TFAD: A Decomposition Time Series Anomaly Detection Architecture with Frequency Analysis
A Multipurpose Library for Synthetic Time Series Generation in Python
Streamlit — A faster way to build and share data apps.
A Python memory profiler for data processing and scientific computing applications
This repository is a list of machine learning libraries written in Rust. It's a compilation of GitHub repositories, blogs, books, movies, discussions, papers, etc. 🦀
Python library for converting Python calculations into rendered latex.
Fixes mojibake and other glitches in Unicode text, after the fact.
Package for Time Series Forecasting and Anomaly Detection Problems.
WWW 2018: Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
A time series generation tool for KPI anomaly detection
Implementation of Peaks-over-Threshold algorithms, including POT, Stream POT (SPOT), and SPOT with Drift (DSPOT).
A Python package for data analysis with permutation entropy and ordinal network methods.