Buchumschlag

MTSpark: Enabling Multi-Task Learning with Spiking Neural Networks for Generalist Agents

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Devkota, Avaneesh, Putra, Rachmad Vidya Wicaksana, Shafique, Muhammad
Format:	Preprint
Veröffentlicht:	2024
Schlagworte:	Neural and Evolutionary Computing Artificial Intelligence Machine Learning
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Scalable Multi-Task Learning through Spiking Neural Networks with Adaptive Task-Switching Policy for Intelligent Autonomous Agents
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2025)

SpikeNAS: A Fast Memory-Aware Neural Architecture Search Framework for Spiking Neural Network-based Embedded AI Systems
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2024)

TopSpark: A Timestep Optimization Methodology for Energy-Efficient Spiking Neural Networks on Autonomous Mobile Agents
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2023)

SpiKernel: A Kernel Size Exploration Methodology for Improving Accuracy of the Embedded Spiking Neural Network Systems
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2024)

NeuroNAS: Enhancing Efficiency of Neuromorphic In-Memory Computing for Intelligent Mobile Agents through Hardware-Aware Spiking Neural Architecture Search
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2024)

SNN4Agents: A Framework for Developing Energy-Efficient Embodied Spiking Neural Networks for Autonomous Agents
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2024)

Enabling Efficient Processing of Spiking Neural Networks with On-Chip Learning on Commodity Neuromorphic Processors for Edge AI Systems
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2025)

QSViT: A Methodology for Quantizing Spiking Vision Transformers
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2025)

FastSpiker: Enabling Fast Training for Spiking Neural Networks on Event-based Data through Learning Rate Enhancements for Autonomous Embedded Systems
von: Bano, Iqra, et al.
Veröffentlicht: (2024)

QSLM: A Performance- and Memory-aware Quantization Framework with Tiered Search Strategy for Spike-driven Language Models
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2026)

A Methodology to Study the Impact of Spiking Neural Network Parameters considering Event-Based Automotive Data
von: Bano, Iqra, et al.
Veröffentlicht: (2024)

PENDRAM: Enabling High-Performance and Energy-Efficient Processing of Deep Neural Networks through a Generalized DRAM Data Mapping Policy
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2024)

SpikeVox: Towards Energy-Efficient Speech Therapy Framework with Spike-driven Generative Language Models
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2025)

Continual Learning with Neuromorphic Computing: Foundations, Methods, and Emerging Applications
von: Minhas, Mishal Fatima, et al.
Veröffentlicht: (2024)

Replay4NCL: An Efficient Memory Replay-based Methodology for Neuromorphic Continual Learning in Embedded AI Systems
von: Minhas, Mishal Fatima, et al.
Veröffentlicht: (2025)

Embodied Neuromorphic Artificial Intelligence for Robotics: Perspectives, Challenges, and Research Development Stack
von: Putra, Rachmad Vidya Wicaksana, et al.
Veröffentlicht: (2024)

Focus Session: Hardware and Software Techniques for Accelerating Multimodal Foundation Models
von: Shafique, Muhammad, et al.
Veröffentlicht: (2026)

TACOS: Task Agnostic Continual Learning in Spiking Neural Networks
von: Soures, Nicholas, et al.
Veröffentlicht: (2024)

Gradient-Free Continual Learning in Spiking Neural Networks via Inter-Spike Interval Regularization
von: Roy, Samrendra, et al.
Veröffentlicht: (2026)

Spark: Modular Spiking Neural Networks
von: Franco, Mario, et al.
Veröffentlicht: (2026)

Continuous Spiking Graph Neural Networks
von: Yin, Nan, et al.
Veröffentlicht: (2024)

Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks
von: Xiao, Mingqing, et al.
Veröffentlicht: (2024)

Scalable Learning in Structured Recurrent Spiking Neural Networks without Backpropagation
von: Tang, Bo, et al.
Veröffentlicht: (2026)

Enhancing Graph Representation Learning with Attention-Driven Spiking Neural Networks
von: Yin, Huifeng, et al.
Veröffentlicht: (2024)

A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
von: Li, Jintang, et al.
Veröffentlicht: (2023)

Quantum-Evolutionary Neural Networks for Multi-Agent Federated Learning
von: Lala, Aarav, et al.
Veröffentlicht: (2025)

Geometry-Aware Spiking Graph Neural Network
von: Zhang, Bowen, et al.
Veröffentlicht: (2025)

Dynamic Spiking Framework for Graph Neural Networks
von: Yin, Nan, et al.
Veröffentlicht: (2023)

The Robustness of Spiking Neural Networks in Communication and its Application towards Network Efficiency in Federated Learning
von: Nguyen, Manh V., et al.
Veröffentlicht: (2024)

Adversarially Robust Spiking Neural Networks Through Conversion
von: Özdenizci, Ozan, et al.
Veröffentlicht: (2023)

TESS: A Scalable Temporally and Spatially Local Learning Rule for Spiking Neural Networks
von: Apolinario, Marco Paul E., et al.
Veröffentlicht: (2025)

The Enduring Dominance of Deep Neural Networks: A Critical Analysis of the Fundamental Limitations of Quantum Machine Learning and Spiking Neural Networks
von: Ishikawa, Takehiro
Veröffentlicht: (2025)

STAER: Temporal Aligned Rehearsal for Continual Spiking Neural Network
von: Gianferrari, Matteo, et al.
Veröffentlicht: (2026)

Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning
von: Xiao, Mingqing, et al.
Veröffentlicht: (2024)

Backpropagation-free Spiking Neural Networks with the Forward-Forward Algorithm
von: Ghader, Mohammadnavid, et al.
Veröffentlicht: (2025)

Understanding the Functional Roles of Modelling Components in Spiking Neural Networks
von: Yin, Huifeng, et al.
Veröffentlicht: (2024)

SiGNN: A Spike-induced Graph Neural Network for Dynamic Graph Representation Learning
von: Chen, Dong, et al.
Veröffentlicht: (2024)

SPEAR: Structured Pruning for Spiking Neural Networks via Synaptic Operation Estimation and Reinforcement Learning
von: Xie, Hui, et al.
Veröffentlicht: (2025)

Average-Over-Time Spiking Neural Networks for Uncertainty Estimation in Regression
von: Sun, Tao, et al.
Veröffentlicht: (2024)

A Scalable Hybrid Training Approach for Recurrent Spiking Neural Networks
von: Baronig, Maximilian, et al.
Veröffentlicht: (2025)