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08/31/2023
Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning
We introduce a method to convert Physics-Informed Neural Networks (PINNs...
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05/26/2023
Sharing Leaky-Integrate-and-Fire Neurons for Memory-Efficient Spiking Neural Networks
Spiking Neural Networks (SNNs) have gained increasing attention as energ...
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05/26/2023
Do We Really Need a Large Number of Visual Prompts?
Due to increasing interest in adapting models on resource-constrained ed...
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05/11/2023
Divide-and-Conquer the NAS puzzle in Resource Constrained Federated Learning Systems
Federated Learning (FL) is a privacy-preserving distributed machine lear...
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04/25/2023
Uncovering the Representation of Spiking Neural Networks Trained with Surrogate Gradient
Spiking Neural Networks (SNNs) are recognized as the candidate for the n...
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04/02/2023
SEENN: Towards Temporal Spiking Early-Exit Neural Networks
Spiking Neural Networks (SNNs) have recently become more popular as a bi...
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03/30/2023
XPert: Peripheral Circuit Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing
The hardware-efficiency and accuracy of Deep Neural Networks (DNNs) impl...
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02/13/2023
Workload-Balanced Pruning for Sparse Spiking Neural Networks
Pruning for Spiking Neural Networks (SNNs) has emerged as a fundamental ...
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11/26/2022
Exploring Temporal Information Dynamics in Spiking Neural Networks
Most existing Spiking Neural Network (SNN) works state that SNNs may uti...
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11/14/2022
Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks
We study the Human Activity Recognition (HAR) task, which predicts user ...
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07/04/2022
Lottery Ticket Hypothesis for Spiking Neural Networks
Spiking Neural Networks (SNNs) have recently emerged as a new generation...
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06/20/2022
Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars
Spiking Neural Networks (SNNs) have recently emerged as the low-power al...
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04/25/2022
Loss-based Sequential Learning for Active Domain Adaptation
Active domain adaptation (ADA) studies have mainly addressed query selec...
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04/11/2022
SATA: Sparsity-Aware Training Accelerator for Spiking Neural Networks
Spiking Neural Networks (SNNs) have gained huge attention as a potential...
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03/24/2022
Addressing Client Drift in Federated Continual Learning with Adaptive Optimization
Federated learning has been extensively studied and is the prevalent met...
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03/11/2022
Neuromorphic Data Augmentation for Training Spiking Neural Networks
Developing neuromorphic intelligence on event-based datasets with spikin...
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02/09/2022
Adversarial Detection without Model Information
Most prior state-of-the-art adversarial detection works assume that the ...
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01/31/2022
Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?
Recent Spiking Neural Networks (SNNs) works focus on an image classifica...
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01/23/2022
Neural Architecture Search for Spiking Neural Networks
Spiking Neural Networks (SNNs) have gained huge attention as a potential...
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01/05/2022
Gradient-based Bit Encoding Optimization for Noise-Robust Binary Memristive Crossbar
Binary memristive crossbars have gained huge attention as an energy-effi...
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10/14/2021
Beyond Classification: Directly Training Spiking Neural Networks for Semantic Segmentation
Spiking Neural Networks (SNNs) have recently emerged as the low-power al...
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06/11/2021
Federated Learning with Spiking Neural Networks
As neural networks get widespread adoption in resource-constrained embed...
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04/07/2021
PrivateSNN: Fully Privacy-Preserving Spiking Neural Networks
How can we bring both privacy and energy-efficiency to a neural system o...
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03/26/2021
Visual Explanations from Spiking Neural Networks using Interspike Intervals
Spiking Neural Networks (SNNs) compute and communicate with asynchronous...
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10/05/2020
Revisiting Batch Normalization for Training Low-latency Deep Spiking Neural Networks from Scratch
Spiking Neural Networks (SNNs) have recently emerged as an alternative t...
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08/07/2020
Associative Partial Domain Adaptation
Partial Adaptation (PDA) addresses a practical scenario in which the tar...
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07/03/2020
Domain Adaptation without Source Data
Domain adaptation assumes that samples from source and target domains ar...
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05/16/2020
Partial Domain Adaptation Using Graph Convolutional Networks
Partial domain adaptation (PDA), in which we assume the target label spa...
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12/03/2019
Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification
Visible-infrared person re-identification (VI-ReID) is an important task...
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10/12/2019
Combinational Class Activation Maps for Weakly Supervised Object Localization
Weakly supervised object localization has recently attracted attention s...
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10/02/2019
CNN-based Semantic Segmentation using Level Set Loss
Thesedays, Convolutional Neural Networks are widely used in semantic seg...
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09/29/2019
Learning to Align Multi-Camera Domain for Unsupervised Video Person Re-Identification
Most video person re-identification (re-ID) methods are mainly based on ...
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09/29/2019
