incremental-learning | Topic | Ecosyste.ms: Repos

Topic: "incremental-learning"

uiuc-ischool-scanr/SAIL

Sentiment Analysis with Incremental Learning

Language: Java - Size: 20.9 MB - Last synced at: about 2 years ago - Pushed at: over 8 years ago - Stars: 11 - Forks: 9

nazmul-karim170/CNLL-Continual_Learning_Noisy_Labels

Official Implementation of CVPR 2022 workshop paper "CNLL: A Semi-supervised Approach for Continual Noisy Label Learning"

Language: Python - Size: 367 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 10 - Forks: 2

humansensinglab/POET-continual-action-recognition

Code for the paper: "POET: Prompt Offset Tuning for Continual Human Action Adaptation" (ECCV 2024, Oral)

Language: Python - Size: 49.1 MB - Last synced at: 24 days ago - Pushed at: 24 days ago - Stars: 9 - Forks: 1

umbertocappellazzo/CL_Anthology

An anthology of recent continual learning papers, where people interested in this fascinating topic can start discovering its multidimensional representations.

Size: 98.6 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 9 - Forks: 0

jbakams/slimebot-volleyball

3D gym environments to train RL agents to play the Slime Volleyball game in 3 dimensions using Webots as simulator.

Language: Python - Size: 124 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 9 - Forks: 0

wangkai930418/DwoPP_code

code for our BMVC 2022 paper "Positive Pair Distillation Considered Harmful: Continual Meta Metric Learning for Lifelong Object Re-Identification"

Language: Python - Size: 103 KB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 9 - Forks: 1

AyanKumarBhunia/DIY-FSCIL

[CVPR-2022] ''Doodle It Yourself: Class Incremental Learning by Drawing a Few Sketches'', IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2022.

Language: Python - Size: 3.03 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 9 - Forks: 1

abhilashreddys/FSCIL-GFR

Official Code for the paper Few-Shot Class Incremental Learning with Generative Feature Replay

Language: Python - Size: 107 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 9 - Forks: 0

apurba-nsu-rnd-lab/SAN

[ICPR 2022] Official Implementation of the paper "Rethinking Task-Incremental Learning Baselines" accepted in the 26th International Conference on Pattern Recognition.

Language: Python - Size: 31.3 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 8 - Forks: 1

luciainnocenti/Incremental-learning

The main goal of this project is to implement a neural network capable of learning different tasks without forgetting the ones it has learned before.

Language: Jupyter Notebook - Size: 3.46 MB - Last synced at: 9 months ago - Pushed at: about 4 years ago - Stars: 8 - Forks: 0

GhadaSokar/SpaceNet

Implementation for the paper "SpaceNet: Make Free Space For Continual Learning" in PyTorch.

Language: Python - Size: 10.7 KB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 8 - Forks: 0

gauthamkrishna-g/ActiveHARNet

ActiveHARNet: Towards On-Device Deep Bayesian Active Learning for Human Activity Recognition

Language: Jupyter Notebook - Size: 116 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 8 - Forks: 6

val-iisc/GANTree Fork of maharshi95/GANTree

Code for ICCV Paper "GAN-Tree: An Incrementally Learned Hierarchical Generative Framework for Multi-Modal Data Distributions"

Language: Python - Size: 26.7 MB - Last synced at: over 1 year ago - Pushed at: over 5 years ago - Stars: 8 - Forks: 3

NeurAI-Lab/ConsistencyCL

Official repo for "Consistency is the key to further mitigating catastrophic forgetting in continual learning"

Language: Python - Size: 56.6 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 7 - Forks: 1

NeurAI-Lab/TARC

Official repo for "Task Agnostic Representation Consolidation: a Self-supervised based Continual Learning Approach"

Language: Python - Size: 130 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 7 - Forks: 0

shahad-mahmud/incremental_learning_for_asr

Incremental learning for automatic speech recognition (ASR)

Language: Python - Size: 6.42 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 7 - Forks: 1

rom1mouret/orthogonal_learning

continual learning algorithms from CVPR 2021 and ICLR 2021

Language: Python - Size: 18.6 KB - Last synced at: over 1 year ago - Pushed at: almost 4 years ago - Stars: 7 - Forks: 1

szrlee/awesome-continual-learning 📦

Resources collection for the hot research topic of Continual Learning, a fundamental step stone to Artificial General Intelligence (AGI).

Size: 1000 Bytes - Last synced at: 12 days ago - Pushed at: over 6 years ago - Stars: 7 - Forks: 3

Czi24/VLLM-IL

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

Size: 14.6 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 6 - Forks: 0

LIMr1209/machine-learn

神经网络模型训练研究学习

Language: Python - Size: 22.7 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 6 - Forks: 1

Vision-Intelligence-and-Robots-Group/DCIL

Official implementation of Deep Class Incremental Learning from Decentralized Data (IEEE TNNLS 22)

Language: Python - Size: 468 KB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 6 - Forks: 1

bharathsudharsan/Optimized-One-vs-One-Algorithm

Code for AAAI poster 'Training up to 50 Class ML Models on 3 $ IoT Hardware via Optimizing One-vs-One Algorithm'

Language: C - Size: 1.04 MB - Last synced at: 25 days ago - Pushed at: almost 3 years ago - Stars: 6 - Forks: 0

mrifkikurniawan/sslad

3rd Place Solution for ICCV 2021 Workshop SSLAD Track 3A - Continual Learning Classification Challenge

Language: Jupyter Notebook - Size: 27.5 MB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 6 - Forks: 5

Alessio-Siciliano/Incremental-Learning-iCarl

Language: Python - Size: 469 KB - Last synced at: about 2 months ago - Pushed at: about 4 years ago - Stars: 6 - Forks: 2

GhadaSokar/Self-Attention-Meta-Learner-for-Continual-Learning

Implementation for the paper "Self-Attention Meta-Learner for Continual Learning" in PyTorch.

Language: Python - Size: 1.89 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 6 - Forks: 2

cjbayron/clem.pytorch

Continual Learning methods using Episodic Memory (CLEM) in PyTorch

Language: Jupyter Notebook - Size: 23.4 KB - Last synced at: 3 days ago - Pushed at: about 5 years ago - Stars: 6 - Forks: 0

remiadon/streamz-ml 📦

streaming Machine Learning in python

Language: Python - Size: 17.6 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 6 - Forks: 0

saeedahmadicp/KAN-CL-ViT

Continual Learning with KAN based ViT to mitigate catastrophic forgetting

Language: Python - Size: 37.1 MB - Last synced at: 8 days ago - Pushed at: 11 months ago - Stars: 5 - Forks: 1

EvecloudGroup/evecloud-frontend

Eve is specifically tailored for evidence based effective studying with help of evidence based methods such as: spaced repetition (SM2), interleaved practice and incremental reading.

Language: JavaScript - Size: 2.36 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 5 - Forks: 0

andre-b-fernandes/FEUP-DISS

Software library for stream-based recommender systems

Language: Python - Size: 1.4 MB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 5 - Forks: 1

sylwekczmil/sevq

Simple Evolving Vector Quantization

Language: Python - Size: 4.56 MB - Last synced at: 23 days ago - Pushed at: about 3 years ago - Stars: 5 - Forks: 1

gauthamkrishna-g/HARNet

HARNet: Towards On-Device Incremental Learning using Deep Ensembles on Constrained Devices for Human Activity Recognition

Language: Jupyter Notebook - Size: 20.5 KB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 5 - Forks: 8

LivingCryogen/Hazard

Hazard! is a local "hot-seat" game for two to six players developed using Windows Presentation Foundation (WPF).

Language: C# - Size: 182 MB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 4 - Forks: 0

expectopatronm/accelerated-incremental-learning-with-support-vector-machines

Accelerated implementation of the SVM algorithm on an embedded SoC with changes to the algorithm structure to accommodate learning from large volumes of data in an incremental manner with approximations to the computations.

Language: VHDL - Size: 738 MB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 1

jchambyd/IGMN-NSE

Incremental Gaussian Mixture Network for Non-Stationary Environments

Language: Java - Size: 75.1 MB - Last synced at: almost 2 years ago - Pushed at: over 6 years ago - Stars: 4 - Forks: 0

libo-huang/Awesome-Causal-Incremental-Learning

Awesome Causal Incremental / Continual / Lifelong Learning

Size: 22.5 KB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 3 - Forks: 1

muratonuryildirim/FOCIL

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

Language: Python - Size: 1.2 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 3 - Forks: 0

libo-huang/Awesome-Incremental-Generative-Learning

Awesome Incremental / Continual / Lifelong Generative Learning

Size: 187 KB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 3 - Forks: 1

oflg/fishing-catchfish 📦

Integrate Incremental Reading into TiddlyWiki

Size: 73.2 KB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0

oflg/fishing-analysis 📦

Analysis for Fishing

Language: JavaScript - Size: 38.1 KB - Last synced at: about 1 year ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

wangkai930418/ERD

code for our paper "Incremental Meta-Learning via Episodic Replay Distillation for Few-Shot Image Recognition" in CVPR 2022 3rd CLVISION continual learning workshop

Language: Python - Size: 1.99 MB - Last synced at: about 1 month ago - Pushed at: almost 3 years ago - Stars: 3 - Forks: 0

mmasana/Class-Orderings

Code from "On Class Orderings for Incremental Learning", CL-ICML 2020

Language: Jupyter Notebook - Size: 4.08 MB - Last synced at: about 2 months ago - Pushed at: about 3 years ago - Stars: 3 - Forks: 0

NaquibAlam/LightGBM-and-Xgboost-advanced-examples

Contains the examples which covers how to incrementally train, how to implement learning_rate scheduler, and how to implement custom objective and evaluation function in case of lightgbm/xgboost models.

Language: Jupyter Notebook - Size: 242 KB - Last synced at: about 1 year ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 0

danielegenta/Progetto-MLDL

Implementation of iCaRL

Language: Jupyter Notebook - Size: 37.9 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 2

vidit98/Lifelong_Object_Recognition

Repo for competition track Lifelong Robotic Vision, IROS 2019.

Language: Python - Size: 130 KB - Last synced at: 2 months ago - Pushed at: about 5 years ago - Stars: 3 - Forks: 0

camilonar/DILF

Framework for Incremental Learning in Deep Learning using TensorFlow

Language: Python - Size: 436 KB - Last synced at: about 2 years ago - Pushed at: almost 6 years ago - Stars: 3 - Forks: 4

gorodnichy/PINN

Open Source C++ Library for Pseudo-inverse Fully Connected Recurrent Neural Networks (from my PhD)

Language: C++ - Size: 4.17 MB - Last synced at: about 2 years ago - Pushed at: almost 7 years ago - Stars: 3 - Forks: 0

tassa-yoniso-manasi-karoto/irgen

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

Language: Go - Size: 18.5 MB - Last synced at: about 1 month ago - Pushed at: 6 months ago - Stars: 2 - Forks: 0

khaendler/HoeffdingPruningTree

An extension of the Hoeffding tree that prunes itself based on feature importance.

Language: Python - Size: 53.7 KB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 2 - Forks: 0

csiro-robotics/SDCL

[Neural Networks 2023] The official repository of Neural Networks Journal "Subspace Distillation for Continual Learning"

Language: Python - Size: 298 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 2 - Forks: 0

Dacaidi/LRFR

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

Language: Python - Size: 61.5 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

csiro-robotics/L3DMC

🤖[MICCAI 2023] The official repository for paper "L3DMC: Lifelong Learning using Distillation via Mixed-Curvature Space"

Language: Python - Size: 536 KB - Last synced at: 11 months ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

ImMohammadHosseini/incremental-learning

:sparkles: Implementation of "Learn#: A Novel incremental learning method for text classification". Its includes four components: :heavy_check_mark:Student model (deep learning :fire:), :heavy_check_mark: a reinforcement learning (RL) module, :heavy_check_mark:a Teacher model, and :heavy_check_mark: a discriminator model.

Language: PureBasic - Size: 32 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

DRLib/StreamDR

Implementation of StreamDR - A Multi-level Parallel Framework for Streaming High-dimensional Data Visualization

Language: Python - Size: 46.5 MB - Last synced at: almost 2 years ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

oflg/fishing-twpub 📦

Import TWPUB books to Fishing for Incremental Reading

Size: 37.1 KB - Last synced at: about 1 year ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

San411/Predicting-Poverty-Replication

Predicting poverty using satellite images for African Countries

Language: Jupyter Notebook - Size: 3.17 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 1

AlgoMathITMO/DPRank

This repository provides an implementation of algorithmic support for dynamic pricing based on surrogate ticket demand modeling for a passenger rail company on open data.

Language: Jupyter Notebook - Size: 61.9 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 3

GhadaSokar/AFAF

[ECMLPKDD 2022] "Avoiding Forgetting and Allowing Forward Transfer in Continual Learning via Sparse Networks" by by Ghada Sokar, Decebal Constantin Mocanu, and Mykola Pechenizkiy.

Language: Python - Size: 21.5 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

agrudkow/Cost-Free-Incremental-Learning Fork of MozhganPourKeshavarz/Cost-Free-Incremental-Learning

Cost-Free Incremental Learning

Language: Jupyter Notebook - Size: 4.24 MB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 2 - Forks: 0

emanuele-progr/Data-Incremental-Learning

A python framework for dealing and experimenting with image classification in a data-incremental scenario.

Language: Python - Size: 4.29 MB - Last synced at: 11 days ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

rom1mouret/domain_IL

thoughts on continual learning and experiments.

Language: Python - Size: 343 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 1

agusticonesagago/Evaluation-of-methods-to-combine-predictions-from-ensemble-learning-in-multivariate-forecasting

This project studies different possibilities to make good predictions based on machine learning algorithms, but without requiring great theoretical knowledge from the users. Moreover, a software package that implements the prediction process has been developed. The software is an ensemble method that first predicts a value taking into account different algorithms at the same time, and then it combines their results considering also the previous performance of each algorithm to obtaina final prediction of the value. Moreover, the solution proposed and implemented in this project can also predict according to a concrete objective (e.g., optimize theprediction, or do not exceed the real value) because not every prediction problem is subject to the same constraints. We have experimented and validated the implementation with three different cases. In all of them, a better performance has been obtained in comparison with each of the algorithms involved, reaching improvements of 45 to 95%.

Language: Jupyter Notebook - Size: 2.18 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 1