ffyoko

parapply

A simple drop-in replacement for pandas `apply()`, parallelized using `joblib`.

multiprocesspandas

Adds multiprocessing capabilities to Pandas to parallelize apply operations on DataFrames, Series and DataFrameGroupBy

asv-subtools

An Open Source Tools for Speaker Recognition

MultiObjectiveOptimization

Source code for Neural Information Processing Systems (NeurIPS) 2018 paper "Multi-Task Learning as Multi-Objective Optimization"

MiniCPM

MiniCPM3-4B: An edge-side LLM that surpasses GPT-3.5-Turbo.

K-BERT

Source code of K-BERT (AAAI2020)

Ant-Debiased-Causal-Tree

Ranger-Deep-Learning-Optimizer

Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase

CRATE

Code for CRATE (Coding RAte reduction TransformEr).

picoGPT

An unnecessarily tiny implementation of GPT-2 in NumPy.

mvts_transformer

Multivariate Time Series Transformer, public version

TimeSeriesEmbedding

PyTorch implementation of "Unsupervised Scalable Representation Learning for Multivariate Time Series" by Franceschi, Dieuleveut, and Jaggi (2020) (https://arxiv.org/pdf/1901.10738v4.pdf).

UnsupervisedScalableRepresentationLearningTimeSeries

Unsupervised Scalable Representation Learning for Multivariate Time Series: Experiments

TNC_TS_baseline

A modification of the TNC model from "UNSUPERVISED REPRESENTATION LEARNING FOR TIME SERIES WITH TEMPORAL NEIGHBORHOOD CODING" for baseline results to be used in our study

TS-TCC

[IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"

ts2vec

A universal time series representation learning framework

forecastxgb-py

pytorch-distributed

A quickstart and benchmark for pytorch distributed training.

GraphZoom

GraphZoom: A Multi-level Spectral Approach for Accurate and Scalable Graph Embedding

Graph-Neural-Network

offsite-tuning

Offsite-Tuning: Transfer Learning without Full Model

LAVIS

LAVIS - A One-stop Library for Language-Vision Intelligence

python-causality-handbook

Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.

36-methods-for-data-analysis

cfrnet-reproduction

Reproducing Shalit et al.'s Individual Treatment Effect model. This is a deep neural net that can be applied to various problems in causal inference.

ms-predictive-enrichment

Code for the paper by Falet et al. (2022) "Estimating treatment effect for individuals with progressive multiple sclerosis using deep learning"

causalml

Uplift modeling and causal inference with machine learning algorithms

CausalDiscoveryToolbox

Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

awesome-causality-algorithms

An index of algorithms for learning causality with data

InvPref_KDD_2022

KDD 2022 Invariant Preference Learning for General Debiasing in Recommendation