Search Results for author:
Found 7 papers, 4 papers with code
Automatic Data Augmentation by Learning the Deterministic Policy
By introducing an unified optimization goal, DeepAugNet intends to combine the data augmentation and the deep model training in an end-to-end training manner which is realized by simultaneously training a hybrid architecture of dueling deep Q-learning algorithm and a surrogate deep model.
Automatic Data Augmentation via Deep Reinforcement Learning for Effective Kidney Tumor Segmentation
Conventional data augmentation realized by performing simple pre-processing operations (\eg, rotation, crop, \etc) has been validated for its advantage in enhancing the performance for medical image segmentation.
Diversity Helps: Unsupervised Few-shot Learning via Distribution Shift-based Data Augmentation
Importantly, we highlight the value and importance of the distribution diversity in the augmentation-based pretext few-shot tasks, which can effectively alleviate the overfitting problem and make the few-shot model learn more robust feature representations.
Data Augmentation
Unsupervised Few-Shot Image Classification
+1
LibFewShot: A Comprehensive Library for Few-shot Learning
Furthermore, based on LibFewShot, we provide comprehensive evaluations on multiple benchmarks with various backbone architectures to evaluate common pitfalls and effects of different training tricks.
Generalizing to Evolving Domains with Latent Structure-Aware Sequential Autoencoder
Domain generalization aims to improve the generalization capability of machine learning systems to out-of-distribution (OOD) data.
Learning Dynamic Graph Embeddings with Neural Controlled Differential Equations
Empirical evaluation on a range of dynamic graph representation learning tasks demonstrates the superiority of our proposed approach compared to the baselines.
Log Neural Controlled Differential Equations: The Lie Brackets Make a Difference
The core component of Log-NCDEs is the Log-ODE method, a tool from the study of rough paths for approximating a CDE's solution.
