Popular GitHub Repositories for Incremental Variable Elimination

? Online machine learning in Python

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

? TensorFlow Code for technical report: "YOLOv3: An Incremental Improvement"

LakeSoul is an end-to-end, realtime and cloud native Lakehouse framework with fast data ingestion, concurrent update and incremental data analytics on cloud storages for both BI and AI applications.

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO?

(CVPR 2021 Oral) Open World Object Detection

PyCIL: A Python Toolbox for Class-Incremental Learning

Library for streaming data and incremental learning algorithms.

Pixeltable — AI Data infrastructure providing a declarative, incremental approach for multimodal workloads.

Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 baselines.

Evaluate three types of task shifting with popular continual learning algorithms.

Code for PaperRobot: Incremental Draft Generation of Scientific Ideas

? PILOT: A Pre-trained Model-Based Continual Learning Toolbox

GIF is a photorealistic generative face model with explicit 3D geometric and photometric control.

A collection of online continual learning paper implementations and tricks for computer vision in PyTorch, including our ASER(AAAI-21), SCR(CVPR21-W) and an online continual learning survey (Neurocomputing).

A collection of incremental learning paper implementations including PODNet (ECCV20) and Ghost (CVPR-W21).

DGMs for NLP. A roadmap.

Official implementation of "DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents"

DIVA: A Dirichlet Process Mixtures Based Incremental Deep Clustering Algorithm via Variational Auto-Encoder