114 Open source projects that are alternatives of or similar to class-incremental-learning

Continual learning baselines and strategies from popular papers, using Avalanche. We include EWC, SI, GEM, AGEM, LwF, iCarl, GDumb, and other strategies.

Open-source code for our paper: Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition

No description or website provided.

Official Implementation of Remembering for the Right Reasons (ICLR 2021)

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

Repository containing code for the paper "Meta-Learning with Sparse Experience Replay for Lifelong Language Learning".

Lagrangian VAE

(RecSys 2020) Adaptively Distilled Exemplar Replay towards Continual Learning for Session-based Recommendation [Best Short Paper]

CVPR 2020 Continual Learning Challenge - Submit your CL algorithm today!

Implementation of a convolutional Variational-Autoencoder model in pytorch.

Software for managing music metadata, registration/licencing of musical works and royalty processing.

CVAE_XGate model in paper "Xu, Dusek, Konstas, Rieser. Better Conversations by Modeling, Filtering, and Optimizing for Coherence and Diversity"

AE and VAE Playground in PyTorch

Variational autoencoder for Lego minifig faces

Variational autoencoder, denoising autoencoder and other variations of autoencoders implementation in keras

Text Variational Autoencoder inspired by the paper 'Generating Sentences from a Continuous Space' Bowman et al. https://arxiv.org/abs/1511.06349

A PyTorch implementation of "Multimodal Generative Models for Scalable Weakly-Supervised Learning" (https://arxiv.org/abs/1802.05335)

PyTorch implementation of our Adam-NSCL algorithm from our CVPR2021 (oral) paper "Training Networks in Null Space for Continual Learning"

CALC2.0: Combining Appearance, Semantic and Geometric Information for Robust and Efficient Visual Loop Closure

PyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"

NMA deep learning course

Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

Assessing Generative Models via Precision and Recall (official repository)

Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

PyTorch implementation of normalizing flow models

[ WSDM '19 ] Sequential Variational Autoencoders for Collaborative Filtering

Official code of CVPR 2021's PLOP: Learning without Forgetting for Continual Semantic Segmentation

Learning about Haskell with Variational Autoencoders

Official Implementation of CVPR2021 paper: Continual Learning via Bit-Level Information Preserving

Code for our paper -- Hyperprior Induced Unsupervised Disentanglement of Latent Representations (AAAI 2019)

Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)

An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU) in ICLR 2017.

A pytorch compatible data loader to create sequence of tasks for Continual Learning

Implementation of "Disentangled Representation Learning for Non-Parallel Text Style Transfer(ACL 2019)" in Pytorch

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

An implementation of VAEGAN (variational autoencoder + generative adversarial network).

Invariant representation learning from imaging and spectral data

Steven C. Y. Hung, Cheng-Hao Tu, Cheng-En Wu, Chien-Hung Chen, Yi-Ming Chan, and Chu-Song Chen, "Compacting, Picking and Growing for Unforgetting Continual Learning," Thirty-third Conference on Neural Information Processing Systems, NeurIPS 2019

IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

Variational autoencoder for anomaly detection (in PyTorch).

Torch Implemention of ECCV'16 paper: Attribute2Image

One Person, One Model, One World: Learning Continual User Representation without Forgetting

Shared Latent Space VAE's

[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

Variational Neural Machine Translation System

If you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!

Implementation of 'Self-Adversarial Variational Autoencoder with Gaussian Anomaly Prior Distribution for Anomaly Detection'

Keras implementation of a Variational Auto Encoder with a Concrete Latent Distribution

VAE with RealNVP prior and Super-Resolution VAE in PyTorch. Code release for https://arxiv.org/abs/2006.05218.

Using neural network to build expressive hierarchical distribution; A variational method to accurately estimate posterior uncertainty; A fast and general method for Bayesian inference. (ICML 2018)

PyTorch implementation of our CVPR2021 (oral) paper "Prototype Augmentation and Self-Supervision for Incremental Learning"

Interactive exploration of MNIST variational autoencoder latent space with React and tensorflow.js.

Experiments with Adversarial Autoencoders using Keras

There are C language computer programs about the simulator, transformation, and test statistic of continuous Bernoulli distribution. More than that, the book contains continuous Binomial distribution and continuous Trinomial distribution.

An Introduction to Deep Generative Modeling: Examples

music generation with a classifying variational autoencoder (VAE) and LSTM

Timbre transfer with variational autoencoding and cycle-consistent adversarial networks. Able to transfer the timbre of an audio source to that of another.

We got a stew going!

Official Code Repository for "Gradient Projection Memory for Continual Learning"