Youngeun Kim

P. Panda, Abhiroop Bhattacharjee, Yeshwanth Venkatesha, 2022, ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Revisiting Batch Normalization for Training Low-Latency Deep Spiking Neural Networks From Scratch

P. Panda, Youngeun Kim, 2020, Frontiers in Neuroscience.

2022 roadmap on neuromorphic computing and engineering

Gouhei Tanaka, Mufti Mahmud, Chiara Bartolozzi, 2021, Neuromorph. Comput. Eng..

PrivateSNN: Privacy-Preserving Spiking Neural Networks

P. Panda, Yeshwanth Venkatesha, Youngeun Kim, 2021, AAAI.

Visual explanations from spiking neural networks using inter-spike intervals

Priyadarshini Panda, Youngeun Kim, P. Panda, 2021, Scientific Reports.

Progressive Domain Adaptation from a Source Pre-trained Model.

Sungeun Hong, Priyadarshini Panda, Youngeun Kim, 2020 .

NEAT: Nonlinearity Aware Training for Accurate, Energy-Efficient, and Robust Implementation of Neural Networks on 1T-1R Crossbars

Priyadarshini Panda, Abhiroop Bhattacharjee, Lakshya Bhatnagar, 2022, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification

Changick Kim, Seokeon Choi, Sumin Lee, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Beyond classification: directly training spiking neural networks for semantic segmentation pdf

Priyadarshini Panda, Youngeun Kim, Joshua Chough, 2021, Neuromorph. Comput. Eng..

Federated Learning With Spiking Neural Networks

Leandros Tassiulas, Priyadarshini Panda, Youngeun Kim, 2021, IEEE Transactions on Signal Processing.

PrivateSNN: Fully Privacy-Preserving Spiking Neural Networks pdf

Priyadarshini Panda, Youngeun Kim, Yeshwanth Venkatesha, 2021, ArXiv.

SEENN: Towards Temporal Spiking Early-Exit Neural Networks

P. Panda, Youngeun Kim, Yuhang Li, 2023, ArXiv.

Towards Privacy-Preserving Domain Adaptation

Sungeun Hong, Youngeun Kim, Donghyeon Cho, 2020, IEEE Signal Processing Letters.

Wearable-based Human Activity Recognition with Spatio-Temporal Spiking Neural Networks

P. Panda, Youngeun Kim, Yuhang Li, 2022, ArXiv.

Examining the Robustness of Spiking Neural Networks on Non-ideal Memristive Crossbars

P. Panda, Abhiroop Bhattacharjee, Abhishek Moitra, 2022, ISLPED.

Addressing Client Drift in Federated Continual Learning with Adaptive Optimization

P. Panda, Yeshwanth Venkatesha, Youngeun Kim, 2022, ArXiv.

Gradient-based Bit Encoding Optimization for Noise-Robust Binary Memristive Crossbar

Priyadarshini Panda, Youngeun Kim, Hyunsoo Kim, 2022, 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE).

Sharing leaky-integrate-and-fire neurons for memory-efficient spiking neural networks

P. Panda, Abhishek Moitra, Youngeun Kim, 2023, Frontiers in neuroscience.

Do We Really Need a Large Number of Visual Prompts?

P. Panda, Abhishek Moitra, Youngeun Kim, 2023, ArXiv.

XPert: Peripheral Circuit & Neural Architecture Co-search for Area and Energy-efficient Xbar-based Computing

P. Panda, Abhiroop Bhattacharjee, Abhishek Moitra, 2023, arXiv.org.

CNN-Based Semantic Segmentation Using Level Set Loss

Seunghyeon Kim, Youngeun Kim, Changick Kim, 2019, 2019 IEEE Winter Conference on Applications of Computer Vision (WACV).

Adaptive Graph Adversarial Networks for Partial Domain Adaptation

Youngeun Kim, Sungeun Hong, Sungeun Hong, 2021, IEEE Transactions on Circuits and Systems for Video Technology.

Combinational Class Activation Maps for Weakly Supervised Object Localization

Changick Kim, Youngeun Kim, Seunghan Yang, 2019, 2020 IEEE Winter Conference on Applications of Computer Vision (WACV).

Optimizing Deeper Spiking Neural Networks for Dynamic Vision Sensing

Priyadarshini Panda, Youngeun Kim, P. Panda, 2021, Neural Networks.

TL-ADA: Transferable Loss-based Active Domain Adaptation

Dongyoon Han, Sungeun Hong, Youngeun Kim, 2023, Neural Networks.

Examining the Role and Limits of Batchnorm Optimization to Mitigate Diverse Hardware-noise in In-memory Computing

P. Panda, Abhiroop Bhattacharjee, Yeshwanth Venkatesha, 2023, ACM Great Lakes Symposium on VLSI.

Workload-Balanced Pruning for Sparse Spiking Neural Networks

P. Panda, Abhishek Moitra, N. Satpute, 2023, IEEE Transactions on Emerging Topics in Computational Intelligence.

Self-Training Of Graph Neural Networks Using Similarity Reference For Robust Training With Noisy Labels

Changick Kim, Youngeun Kim, Hyoungseob Park, 2020, 2020 IEEE International Conference on Image Processing (ICIP).

Efficient human activity recognition with spatio-temporal spiking neural networks

P. Panda, Youngeun Kim, Yuhang Li, 2023, Frontiers in neuroscience.

StableQ: Enhancing Data-Scarce Quantization with Text-to-Image Data

P. Panda, Youngeun Kim, Yuhang Li, 2023, 2312.05272.

Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification

Changick Kim, Seokeon Choi, Sumin Lee, 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Bilinear Siamese Networks with Background Suppression for Visual Object Tracking

Changick Kim, Seokeon Choi, Youngeun Kim, 2019, BMVC.

SEENN: Towards Temporal Spiking Early-Exit Neural Networks

P. Panda, Youngeun Kim, Yuhang Li, 2023, NeurIPS.

TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training

P. Panda, Abhishek Moitra, Youngeun Kim, 2024, Design, Automation and Test in Europe.

RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems

P. Panda, Abhiroop Bhattacharjee, Abhishek Moitra, 2023, IEEE Transactions on Emerging Topics in Computational Intelligence.

Adversarial Detection without Model Information

P. Panda, Abhishek Moitra, Youngeun Kim, 2022, ArXiv.

GenQ: Quantization in Low Data Regimes with Generative Synthetic Data

P. Panda, Souvik Kundu, Youngeun Kim, 2023, 2312.05272.

Divide-and-Conquer the NAS puzzle in Resource Constrained Federated Learning Systems

P. Panda, Yeshwanth Venkatesha, Youngeun Kim, 2023, Neural Networks.