Multi-Task Learning ML Frameworks
Frameworks, libraries, and optimization methods for training models on multiple related tasks simultaneously. Includes MTL architectures, loss weighting strategies, gradient aggregation, and Pareto optimization. Does NOT include single-task learning, weight space learning as a standalone technique, or continual learning frameworks.
There are 46 multi-task learning frameworks tracked. 4 score above 50 (established tier). The highest-rated is zeiss-microscopy/OAD at 58/100 with 162 stars.
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| # | Framework | Score | Tier |
|---|---|---|---|
| 1 |
zeiss-microscopy/OAD
Collection of tools and scripts useful to automate microscopy workflows in... |
|
Established |
| 2 |
median-research-group/LibMTL
A PyTorch Library for Multi-Task Learning |
|
Established |
| 3 |
qdrant/quaterion
Blazing fast framework for fine-tuning similarity learning models |
|
Established |
| 4 |
lucidrains/PoPE-pytorch
Efficient implementation (and explorations) into polar coordinate positional... |
|
Established |
| 5 |
MR-HosseinzadehTaher/BenchmarkTransferLearning
Official PyTorch Implementation and Pre-trained Models for Benchmarking... |
|
Emerging |
| 6 |
edouardelasalles/stnn
Code for the paper "Spatio-Temporal Neural Networks for Space-Time Series... |
|
Emerging |
| 7 |
Mikoto10032/AutomaticWeightedLoss
Multi-task learning using uncertainty to weigh losses for scene geometry and... |
|
Emerging |
| 8 |
Zehong-Wang/Awesome-Weight-Space-Learning
A collection of weight space learning including papers, codes, and datasets. |
|
Emerging |
| 9 |
snimu/rebasin
Apply methods described in "Git Re-basin"-paper [1] to arbitrary models ---... |
|
Emerging |
| 10 |
thuml/awesome-multi-task-learning
A curated list of DATASETS, CODEBASES and PAPERS on Multi-Task Learning... |
|
Emerging |
| 11 |
mbs0221/Multitask-Learning
Awesome Multitask Learning Resources |
|
Emerging |
| 12 |
david-knigge/ccnn
Code repository of the paper "Modelling Long Range Dependencies in ND: From... |
|
Emerging |
| 13 |
WeiHongLee/Awesome-Multi-Task-Learning
An up-to-date list of works on Multi-Task Learning |
|
Emerging |
| 14 |
TatsuyaShirakawa/poincare-embedding
Poincaré Embedding (unofficial) |
|
Emerging |
| 15 |
samuela/git-re-basin
Code release for "Git Re-Basin: Merging Models modulo Permutation Symmetries" |
|
Emerging |
| 16 |
joelowj/mtl-tsmom
Multi Task Learning Time Series Momentum |
|
Emerging |
| 17 |
BioDT/bfm-model
Multi-modal Foundation Model for Biodiversity dynamics forecasting |
|
Emerging |
| 18 |
jianghaojun/Awesome-Parameter-Efficient-Transfer-Learning
A collection of parameter-efficient transfer learning papers focusing on... |
|
Emerging |
| 19 |
ryusudol/Centered-Kernel-Alignment
The Fastest, Memory-efficient Python Library for layer-wise similarity... |
|
Emerging |
| 20 |
SimonVandenhende/Awesome-Multi-Task-Learning
A list of multi-task learning papers and projects. |
|
Emerging |
| 21 |
mit-gfx/ContinuousParetoMTL
[ICML 2020] Efficient Continuous Pareto Exploration in Multi-Task Learning |
|
Emerging |
| 22 |
Rishit-dagli/GLOM-TensorFlow
An attempt at the implementation of GLOM, Geoffrey Hinton's paper for... |
|
Emerging |
| 23 |
AnkurMali/ContinualPTNCN
We introduce Local recurrent Predictive coding model termed as Parallel... |
|
Emerging |
| 24 |
berkanlafci/oadat
OADAT: Experimental and Synthetic Clinical Optoacoustic Data for... |
|
Emerging |
| 25 |
synbol/Awesome-Parameter-Efficient-Transfer-Learning
Collection of awesome parameter-efficient fine-tuning resources. |
|
Emerging |
| 26 |
BioDT/bfm-data
BioCube: A Multimodal Dataset for Biodiversity |
|
Emerging |
| 27 |
Gxinhu/MTL_airfoil_surrogate
Official implementation for the paper: "Enhancing Airfoil Design... |
|
Emerging |
| 28 |
yashkc2025/low_capacity_nn_behavior
Code for paper "Understanding Generalization, Robustness, and... |
|
Emerging |
| 29 |
HSG-AIML/SANE
Code Repository for the ICML 2024 paper: "Towards Scalable and Versatile... |
|
Emerging |
| 30 |
bornabr/CAPC
Context Aware Predictive Coding (CAPC) |
|
Emerging |
| 31 |
deargen/MT-ENet
Repository for "Improving evidential deep learning via multi-task learning,"... |
|
Emerging |
| 32 |
MinaGhadimiAtigh/Hyperbolic-Busemann-Learning
Hyperbolic Busemann Learning with Ideal Prototypes, NeurIPS2021 |
|
Experimental |
| 33 |
HSG-AIML/NeurIPS_2022-Generative_Hyper_Representations
Code Repository for the NeurIPS 2022 paper: "Hyper-Representations as... |
|
Experimental |
| 34 |
ssnl/poisson_quasimetric_embedding
Open source code for paper "On the Learning and Learnability of Quasimetrics". |
|
Experimental |
| 35 |
YeonwooSung/GLOM
PyTorch implementation of GLOM |
|
Experimental |
| 36 |
ovcharenkoo/mtl_low
Multi-task learning for low-frequency extrapolation and elastic model building |
|
Experimental |
| 37 |
HSG-AIML/NeurIPS_2021-Weight_Space_Learning
Code Repository for the NeurIPS 2021 paper: "Self-Supervised Representation... |
|
Experimental |
| 38 |
insaneI5/information-sphere
📊 Analyze and assess information structures with the Information Particle... |
|
Experimental |
| 39 |
changsheng137/information-sphere
🌐 Information-Oriented Sphere System: From Data to Information Paradigm... |
|
Experimental |
| 40 |
sdsds222/WarpPCHIP-Net
WarpPCHIP-Net integrates RNN memory, convolutional extraction, and PCHIP... |
|
Experimental |
| 41 |
Pengxin-Guo/Awesome-Multi-Task-Learning
Paper List for Multi-Task Learning (focus on architectures and optimization for MTL) |
|
Experimental |
| 42 |
glassroom/goom_ssm_rnn
Reference implementation of the deep RNN described in "Generalized Orders of... |
|
Experimental |
| 43 |
davidandym/Multi-Task-Optimization
A (hopefully) relatively straightforward, easy to modify code base for... |
|
Experimental |
| 44 |
sdsds222/Simulated-Smooth-RNN
recurrent memory cell for sequence processing. Its core innovation provides... |
|
Experimental |
| 45 |
eth-siplab/Shift-Invariant_Deep_Learning_on_Time_Series
The official implementation of ICLR2025 paper for shift-invariant neural networks |
|
Experimental |
| 46 |
rbd079/multiparameter_DOT_dataset
Simulated frequency-domain diffuse optical tomography dataset |
|
Experimental |