PyCIL: A Python Toolbox for Class-Incremental Learning

Saliency-driven Experience Replay for Continual Learning (NeurIPS2024)

Writing AI Conference Papers: A Handbook for Beginners

Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights

Code for "Supermasks in Superposition"

[ICML 2023] Parameter-Level Soft-Masking for Continual Learning

Tips for Writing a Research Paper using LaTeX

Unofficial PyTorch implementation of DeepMind's PNAS 2017 paper "Overcoming Catastrophic Forgetting"

Code for NeurIPS 2021 paper "Flattening Sharpness for Dynamic Gradient Projection Memory Benefits Continual Learning".

如何做好科研写好科研文章？发顶刊顶会总结

MLNLP社区用来帮助大家避免论文投稿小错误的整理仓库。 Paper Writing Tips

论文写作与资料分享

Winning SubNetwork (WSN)

[ICLR 2024] Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks

Awesome Incremental Learning

Official implementation of "Multi-Task Learning as a Bargaining Game" [ICML 2022]

Multi-Task Deep Neural Networks for Natural Language Understanding

multi_task_NLP is a utility toolkit enabling NLP developers to easily train and infer a single model for multiple tasks.

A PyTorch Library for Multi-Task Learning

Official PyTorch Implementation for Fast Adaptive Multitask Optimization (FAMO)

Official PyTorch Implementation for Conflict-Averse Gradient Descent (CAGrad)

This in my Demo of Chen et al. "GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks" ICML 2018

Multi-Task Learning Framework on PyTorch. State-of-the-art methods are implemented to effectively train models on multiple tasks.

Code for the InterSpeech 2023 paper: MMER: Multimodal Multi-task learning for Speech Emotion Recognition

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

source code of my blogs 😋😋

PyTorch based toolkit for developing spiking neural networks (SNNs) by training and testing them on speech command recognition tasks