Prompt tuning and adapter tuning have shown great potential in transferr...
Heat extremes are projected to severely impact humanity and with increas...
Semantically coherent out-of-distribution (SCOOD) detection aims to disc...
Human brains respond to semantic features of presented stimuli with diff...
In this article, an efficient transient electricalthermal co-simulation
...
This work presents two astonishing findings on neural networks learned f...
MLP-like models built entirely upon multi-layer perceptrons have recentl...
Non-exemplar class-incremental learning is to recognize both the old and...
Exemplar-based class-incremental learning is to recognize new classes wh...
Deep learning-based methods for low-light image enhancement typically re...
An adaptive interpolation scheme is proposed to accurately calculate the...
Over the past decade, the number of wildfire has increased significantly...
Few-shot class-incremental learning is to recognize the new classes give...
Many recent machine learning models show dynamic shape characteristics.
...
We show in this work that memory intensive computations can result in se...
Few-shot segmentation aims at assigning a category label to each image p...
In this paper, we tackle one-shot texture retrieval: given an example of...
In recent years, there is a surge on machine learning applications in
in...
In this paper, we consider a popular model for collaborative filtering i...
In standard clustering problems, data points are represented by vectors,...