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Found 6 papers, 2 papers with code
Trapped in texture bias? A large scale comparison of deep instance segmentation
In summary we evaluate 68 models on 61 versions of MS COCO for a total of 4148 evaluations.
Learning of Generalizable and Interpretable Knowledge in Grid-Based Reinforcement Learning Environments
Understanding the interactions of agents trained with deep reinforcement learning is crucial for deploying agents in games or the real world.
An object-centric sensitivity analysis of deep learning based instance segmentation
In this study we establish a comprehensive baseline regarding the object-centric robustness of deep learning models for instance segmentation.
Fine-tuning BERT for Low-Resource Natural Language Understanding via Active Learning
Recently, leveraging pre-trained Transformer based language models in down stream, task specific models has advanced state of the art results in natural language understanding tasks.
Enhancing Decision Tree based Interpretation of Deep Neural Networks through L1-Orthogonal Regularization
One obstacle that so far prevents the introduction of machine learning models primarily in critical areas is the lack of explainability.
Low-Resource Text Classification using Domain-Adversarial Learning
Deep learning techniques have recently shown to be successful in many natural language processing tasks forming state-of-the-art systems.
