In my code portfolio, I generally try new techniques and methods in machine learning. I don't like only copying and pasting.

The efficient SMT-based context-bounded model checker (ESBMC)

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

Code for CPAL-2024 paper "Continual Learning with Dynamic Sparse Training: Exploring Algorithms for Effective Model Updates"

🌊 Online machine learning in Python

Code for the paper "FOCIL: Finetune-and-Freeze for Online Class-Incremental Learning by Training Randomly Pruned Sparse Experts"

[ACL2024] A Codebase for Incremental Learning with Large Language Models; Official released code for "Learn or Recall? Revisiting Incremental Learning with Pre-trained Language Models (ACL 2024)", "Incremental Sequence Labeling: A Tale of Two Shifts (ACL 2024 Findings)", and "Concept-1K: A Novel Benchmark for Instance Incremental Learning (arxiv)"

Vision-Language Large Model Incremental Learning(VLLM-IL)

An Incremental Learning, Continual Learning, and Life-Long Learning Repository

[IJCAI 2024] Continual Multimodal Knowledge Graph Construction

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

Implementation of CLAD: A Continual Learning benchmark for Autonomous Driving. A continual classification and detectin track. Provides pure PyTorch, Avalanche and Detectron2 implementations.

Incremental reading card generator for Anki supporting Wikipedia & local HTML files

PyCIL: A Python Toolbox for Class-Incremental Learning

Code and image database for IROS2022 paper "RECALL: Rehearsal-free Continual Learning for Object Classification". A algorithm to learn new object categories on the fly without forgetting the old ones and without the need to save previous images.

Fwumious Wabbit, fast on-line machine learning toolkit written in Rust

The official API of DoubleAdapt (KDD'23), an incremental learning framework for online stock trend forecasting, WITHOUT dependencies on the qlib package.

Official repository for the ICASSP 2024 paper 'Learning a Low-Rank Feature Representation: Achieving Better Trade-Off between Stability and Plasticity in Continual Learning'.

The official repository (in PyTorch) for the ECCV 2020 paper "Reparameterizing Convolutions for Incremental Multi-Task Learning without Task Interference".