Search Results for author:
Found 10 papers, 3 papers with code
Neuro-Inspired Information-Theoretic Hierarchical Perception for Multimodal Learning
Integrating and processing information from various sources or modalities are critical for obtaining a comprehensive and accurate perception of the real world in autonomous systems and cyber-physical systems.
Unlocking Deep Learning: A BP-Free Approach for Parallel Block-Wise Training of Neural Networks
This includes decisions on how to decouple network blocks and which auxiliary networks to use for each block.
Discovering Malicious Signatures in Software from Structural Interactions
Malware represents a significant security concern in today's digital landscape, as it can destroy or disable operating systems, steal sensitive user information, and occupy valuable disk space.
Leader-Follower Neural Networks with Local Error Signals Inspired by Complex Collectives
Motivated by the intricacy of these collectives, we propose a neural network (NN) architecture inspired by the rules observed in nature's collective ensembles.
Neuro-Inspired Hierarchical Multimodal Learning
Integrating and processing information from various sources or modalities are critical for obtaining a comprehensive and accurate perception of the real world.
Fractional dynamics foster deep learning of COPD stage prediction
The authors show that the fractional dynamic deep learning model (FDDLM) achieves a COPD prediction accuracy of 98. 66% and can serve as a robust alternative to spirometry.
ClipCrop: Conditioned Cropping Driven by Vision-Language Model
Image cropping has progressed tremendously under the data-driven paradigm.
Trust-aware Control for Intelligent Transportation Systems
Many intelligent transportation systems are multi-agent systems, i. e., both the traffic participants and the subsystems within the transportation infrastructure can be modeled as interacting agents.
VRoC: Variational Autoencoder-aided Multi-task Rumor Classifier Based on Text
VRoC consists of a co-train engine that trains variational autoencoders (VAEs) and rumor classification components.
LEX-GAN: Layered Explainable Rumor Detector Based on Generative Adversarial Networks
However, the vigorous growth of social media contributes to the fast-spreading and far-reaching rumors.
