We introduce a method to convert Physics-Informed Neural Networks (PINNs...
Spiking Neural Networks (SNNs) have gained increasing attention as
energ...
Due to increasing interest in adapting models on resource-constrained ed...
Federated Learning (FL) is a privacy-preserving distributed machine lear...
Spiking Neural Networks (SNNs) are recognized as the candidate for the
n...
Spiking Neural Networks (SNNs) have recently become more popular as a
bi...
The hardware-efficiency and accuracy of Deep Neural Networks (DNNs)
impl...
Pruning for Spiking Neural Networks (SNNs) has emerged as a fundamental
...
Most existing Spiking Neural Network (SNN) works state that SNNs may uti...
We study the Human Activity Recognition (HAR) task, which predicts user ...
Spiking Neural Networks (SNNs) have recently emerged as a new generation...
Spiking Neural Networks (SNNs) have recently emerged as the low-power
al...
Active domain adaptation (ADA) studies have mainly addressed query selec...
Spiking Neural Networks (SNNs) have gained huge attention as a potential...
Federated learning has been extensively studied and is the prevalent met...
Developing neuromorphic intelligence on event-based datasets with spikin...
Most prior state-of-the-art adversarial detection works assume that the
...
Recent Spiking Neural Networks (SNNs) works focus on an image classifica...
Spiking Neural Networks (SNNs) have gained huge attention as a potential...
Binary memristive crossbars have gained huge attention as an energy-effi...
Spiking Neural Networks (SNNs) have recently emerged as the low-power
al...
As neural networks get widespread adoption in resource-constrained embed...
How can we bring both privacy and energy-efficiency to a neural system o...
Spiking Neural Networks (SNNs) compute and communicate with asynchronous...
Spiking Neural Networks (SNNs) have recently emerged as an alternative t...
Partial Adaptation (PDA) addresses a practical scenario in which the tar...
Domain adaptation assumes that samples from source and target domains ar...
Partial domain adaptation (PDA), in which we assume the target label spa...
Visible-infrared person re-identification (VI-ReID) is an important task...
Weakly supervised object localization has recently attracted attention s...
Thesedays, Convolutional Neural Networks are widely used in semantic
seg...
Most video person re-identification (re-ID) methods are mainly based on
...
In this paper, we introduce a self-supervised approach for video object
...