ExcelsiorCJH's Stars
charles9n/bert-sklearn
a sklearn wrapper for Google's BERT model
FenTechSolutions/CausalDiscoveryToolbox
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
py-why/dowhy
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
siamakz/iVAE
VAEs and nonlinear ICA: a unifying framework
jwwthu/DL4Stock
This is the project for deep learning in stock market prediction.
ksseono/awesome-causal-inference
xcfcode/Summarization-Papers
Summarization Papers
EvilPsyCHo/Deep-Time-Series-Prediction
Seq2Seq, Bert, Transformer, WaveNet for time series prediction.
ritchieng/the-incredible-pytorch
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
ritchieng/deep-learning-wizard
Open source guides/codes for mastering deep learning to deploying deep learning in production in PyTorch, Python, Apptainer, and more.
MilaNLProc/contextualized-topic-models
A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021 (Bianchi et al.).
cruiseresearchgroup/TSCP2
Time Series Change Point Detection based on Contrastive Predictive Coding
pyecharts/pyecharts
🎨 Python Echarts Plotting Library
jvpoulos/causal-ml
Must-read papers and resources related to causal inference and machine (deep) learning
gerrymanoim/exchange_calendars
Calendars for various securities exchanges.
Chogyuwon/OffensEval
SemEval-2019 Task 6
pydantic/pydantic
Data validation using Python type hints
clhchtcjj/BiNE
BiNE: Bipartite Network Embedding
youngerous/Open-domain-QA
Presentation slides of ODQA
logangraham/arXausality
A every-so-often-updated collection of every causality + machine learning paper submitted to arXiv in the recent past.
zhihanyue/ts2vec
A universal time series representation learning framework
raj-shah/senn
Towards Robust Interpretability with Self-Explaining Neural Networks, Alvarez-Melis et al. 2018
MaartenGr/KeyBERT
Minimal keyword extraction with BERT
bab2min/kiwipiepy
Python API for Kiwi
adjidieng/DETM
microsoft/PowerToys
Windows system utilities to maximize productivity
tailintalent/causal
Discovering directional relations via minimum predictive information regularization
iancovert/Neural-GC
Granger causality discovery for neural networks.
rguo12/awesome-causality-algorithms
An index of algorithms for learning causality with data
jakobrunge/tigramite
Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at