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Awesome-Multi-Task-Learning
A list of multi-task learning papers and projects.
https://github.com/SimonVandenhende/Awesome-Multi-Task-Learning
Last synced: 4 days ago
JSON representation
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Workshop
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Survey papers
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Datasets
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Architectures
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Other
- Multi-path Neural Networks for On-device Multi-domain Visual Classification
- Deep multi-task representation learning: A tensor factorisation approach
- Ubernet: Training a universal convolutional neural network for low-, mid-, and high-level vision using diverse datasets and limited memory
- Learning multiple visual domains with residual adapters
- Learning multiple tasks with multilinear relationship networks
- Beyond shared hierarchies: Deep multitask learning through soft layer ordering
- Routing networks: Adaptive selection of non-linear functions for multi-task learning
- Piggyback: Adapting a single network to multiple tasks by learning to mask weights
- Efficient parametrization of multi-domain deep neural networks
- Attentive single-tasking of multiple tasks
- Reparameterizing Convolutions for Incremental Multi-Task Learning without Task Interference
- Exploring Relational Context for Multi-Task Dense Prediction
- Universal Representation Learning from Multiple Domains for Few-shot Classification
- Learning Multiple Dense Prediction Tasks from Partially Annotated Data
- Learning Multiple Dense Prediction Tasks from Partially Annotated Data
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Encoder-based architectures
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Decoder-based architectures
- Integrated perception with recurrent multi-task neural networks
- Pad-net: Multi-tasks guided prediction-and-distillation network for simultaneous depth estimation and scene parsing
- Joint task-recursive learning for semantic segmentation and depth estimation
- Latent multi-task architecture learning
- Pattern-affinitive propagation across depth, surface normal and semantic segmentation
- Pattern-Structure Diffusion for Multi-Task Learning
- MTI-Net: Multi-Scale Task Interaction Networks for Multi-Task Learning
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Neural Architecture Search
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Other
- Fully-adaptive feature sharing in multi-task networks with applications in person attribute classification
- Stochastic filter groups for multi-task cnns: Learning specialist and generalist convolution kernels
- Feature partitioning for efficient multi-task architectures
- Learning to Branch for Multi-Task Learning
- Which Tasks Should Be Learned Together in Multi-task Learning?
- Branched multi-task networks: deciding what layers to share
- Automated Search for Resource-Efficient Branched Multi-Task Networks
- AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning
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Optimization strategies
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Other
- Multi-task learning using uncertainty to weigh losses for scene geometry and semantics
- A modulation module for multi-task learning with applications in image retrieval
- Gradnorm: Gradient normalization for adaptive loss balancing in deep multitask networks
- Multi-task learning as multi-objective optimization
- Adversarial multi-task learning for text classification
- Dynamic task prioritization for multitask learning
- Pareto multi-task learning
- Regularizing Deep Multi-Task Networks using Orthogonal Gradients
- Gradient surgery for multi-task learning
- Just Pick a Sign: Optimizing Deep Multitask Models with Gradient Sign Dropout
- Knowledge Distillation for Multi-task Learning
- InverseForm: A Loss Function for Structured Boundary-Aware Segmentation
- Instance-Level Task Parameters: A Robust Multi-task Weighting Framework
- Instance-Level Task Parameters: A Robust Multi-task Weighting Framework
- Knowledge Distillation for Multi-task Learning
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Transfer learning & Domain Adaptation
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Other
- Large scale fine-grained categorization and domain-specific transfer learning
- Taskonomy: Disentangling task transfer learning
- Task2vec: Task embedding for meta-learning
- Representation similarity analysis for efficient task taxonomy & transfer learning
- Learning to Relate Depth and Semantics for Unsupervised Domain Adaptation
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Robustness
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Other
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