Energy Decay Network (EDeN)
Fuente:
arXiv
Saved in:
| Main Authors: | Shelley, Jamie Nicholas, Consultancy, Optishell |
|---|---|
| Format: | Preprint |
| Published: |
2021
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Neural Optimizer Equation, Decay Function, and Learning Rate Schedule Joint Evolution
by: Morgan, Brandon, et al.
Published: (2024)
by: Morgan, Brandon, et al.
Published: (2024)
All in one timestep: Enhancing Sparsity and Energy efficiency in Multi-level Spiking Neural Networks
by: Castagnetti, Andrea, et al.
Published: (2025)
by: Castagnetti, Andrea, et al.
Published: (2025)
Exploiting Heterogeneity in Timescales for Sparse Recurrent Spiking Neural Networks for Energy-Efficient Edge Computing
by: Chakraborty, Biswadeep, et al.
Published: (2024)
by: Chakraborty, Biswadeep, et al.
Published: (2024)
Spiker-LL: An Energy-Efficient FPGA Accelerator Enabling Adaptive Local Learning in Spiking Neural Networks
by: Caviglia, Alessio, et al.
Published: (2026)
by: Caviglia, Alessio, et al.
Published: (2026)
Energy Costs and Neural Complexity Evolution in Changing Environments
by: Heesom-Green, Sian, et al.
Published: (2025)
by: Heesom-Green, Sian, et al.
Published: (2025)
Maelstrom Networks
by: Evanusa, Matthew, et al.
Published: (2024)
by: Evanusa, Matthew, et al.
Published: (2024)
Application of the Brain Drain Optimization Algorithm to the N-Queens Problem
by: Jolfaei, Sahar Ramezani, et al.
Published: (2025)
by: Jolfaei, Sahar Ramezani, et al.
Published: (2025)
BuildEvo: Designing Building Energy Consumption Forecasting Heuristics via LLM-driven Evolution
by: Lin, Subin, et al.
Published: (2025)
by: Lin, Subin, et al.
Published: (2025)
An Introductory Review of Spiking Neural Network and Artificial Neural Network: From Biological Intelligence to Artificial Intelligence
by: Zheng, Shengjie, et al.
Published: (2022)
by: Zheng, Shengjie, et al.
Published: (2022)
Phythesis: Physics-Guided Evolutionary Scene Synthesis for Energy-Efficient Data Center Design via LLMs
by: LI, Minghao, et al.
Published: (2025)
by: LI, Minghao, et al.
Published: (2025)
Energy-Efficient Digital Design: A Comparative Study of Event-Driven and Clock-Driven Spiking Neurons
by: Marostica, Filippo, et al.
Published: (2025)
by: Marostica, Filippo, et al.
Published: (2025)
Solving nonograms using Neural Networks
by: Rubio, José María Buades, et al.
Published: (2025)
by: Rubio, José María Buades, et al.
Published: (2025)
Weight Decay Regimes in Grokking Transformers: Cheap Online Diagnostics
by: Verma, Lucky
Published: (2026)
by: Verma, Lucky
Published: (2026)
S-AI-Recursive: A Bio-Inspired and Temporal Sparse AI Architecture for Iterative, Introspective, and Energy-Frugal Reasoning
by: Slaoui, Said
Published: (2026)
by: Slaoui, Said
Published: (2026)
Learning Characteristics of Reverse Quaternion Neural Network
by: Yamauchi, Shogo, et al.
Published: (2024)
by: Yamauchi, Shogo, et al.
Published: (2024)
Web Neural Network with Complete DiGraphs
by: Li, Frank
Published: (2024)
by: Li, Frank
Published: (2024)
Learning with Spike Synchrony in Spiking Neural Networks
by: Tian, Yuchen, et al.
Published: (2025)
by: Tian, Yuchen, et al.
Published: (2025)
Parallel Hyperparameter Optimization Of Spiking Neural Network
by: Firmin, Thomas, et al.
Published: (2024)
by: Firmin, Thomas, et al.
Published: (2024)
Continual Learning with Columnar Spiking Neural Networks
by: Larionov, Denis, et al.
Published: (2025)
by: Larionov, Denis, et al.
Published: (2025)
A Survey of Recursive and Recurrent Neural Networks
by: Liu, Jian-wei, et al.
Published: (2025)
by: Liu, Jian-wei, et al.
Published: (2025)
Exploring the Limitations of Layer Synchronization in Spiking Neural Networks
by: Koopman, Roel, et al.
Published: (2024)
by: Koopman, Roel, et al.
Published: (2024)
Spiking Neural Networks: The Future of Brain-Inspired Computing
by: Aribe Jr, Sales G.
Published: (2025)
by: Aribe Jr, Sales G.
Published: (2025)
Dynamics of Structured Complex-Valued Hopfield Neural Networks
by: Garimella, Rama Murthy, et al.
Published: (2025)
by: Garimella, Rama Murthy, et al.
Published: (2025)
k-Winners-Take-All Ensemble Neural Network
by: Agarap, Abien Fred, et al.
Published: (2024)
by: Agarap, Abien Fred, et al.
Published: (2024)
Input-Triggered Hardware Trojan Attack on Spiking Neural Networks
by: Raptis, Spyridon, et al.
Published: (2025)
by: Raptis, Spyridon, et al.
Published: (2025)
Temporal Regularization Training: Unleashing the Potential of Spiking Neural Networks
by: Zhang, Boxuan, et al.
Published: (2025)
by: Zhang, Boxuan, et al.
Published: (2025)
Generalization Bounds of Spiking Neural Networks via Rademacher Complexity
by: Zhang, Shao-Qun, et al.
Published: (2026)
by: Zhang, Shao-Qun, et al.
Published: (2026)
Growing Artificial Neural Networks for Control: the Role of Neuronal Diversity
by: Nisioti, Eleni, et al.
Published: (2024)
by: Nisioti, Eleni, et al.
Published: (2024)
Spikingformer: A Key Foundation Model for Spiking Neural Networks
by: Zhou, Chenlin, et al.
Published: (2023)
by: Zhou, Chenlin, et al.
Published: (2023)
Evolving Efficient Genetic Encoding for Deep Spiking Neural Networks
by: Pan, Wenxuan, et al.
Published: (2024)
by: Pan, Wenxuan, et al.
Published: (2024)
TS-SNN: Temporal Shift Module for Spiking Neural Networks
by: Yu, Kairong, et al.
Published: (2025)
by: Yu, Kairong, et al.
Published: (2025)
Simultaneous Genetic Evolution of Neural Networks for Optimal SFC Embedding
by: Krishnamohan, Theviyanthan, et al.
Published: (2025)
by: Krishnamohan, Theviyanthan, et al.
Published: (2025)
Spike Accumulation Forwarding for Effective Training of Spiking Neural Networks
by: Saiin, Ryuji, et al.
Published: (2023)
by: Saiin, Ryuji, et al.
Published: (2023)
Discrete Differential Evolution Particle Swarm Optimization Algorithm for Energy Saving Flexible Job Shop Scheduling Problem Considering Machine Multi States
by: Wang, Da, et al.
Published: (2025)
by: Wang, Da, et al.
Published: (2025)
Adaptive Reorganization of Neural Pathways for Continual Learning with Spiking Neural Networks
by: Han, Bing, et al.
Published: (2023)
by: Han, Bing, et al.
Published: (2023)
Efficient Disruption of Criminal Networks through Multi-Objective Genetic Algorithms
by: Darmadi, Yehezkiel, et al.
Published: (2026)
by: Darmadi, Yehezkiel, et al.
Published: (2026)
Topological Representations of Heterogeneous Learning Dynamics of Recurrent Spiking Neural Networks
by: Chakraborty, Biswadeep, et al.
Published: (2024)
by: Chakraborty, Biswadeep, et al.
Published: (2024)
Multi-objective Optimal Roadside Units Deployment in Urban Vehicular Networks
by: Guo, Weian, et al.
Published: (2024)
by: Guo, Weian, et al.
Published: (2024)
Dynamic Weight Adaptation in Spiking Neural Networks Inspired by Biological Homeostasis
by: Zhou, Yunduo, et al.
Published: (2025)
by: Zhou, Yunduo, et al.
Published: (2025)
Modular Growth of Hierarchical Networks: Efficient, General, and Robust Curriculum Learning
by: Hamidi, Mani, et al.
Published: (2024)
by: Hamidi, Mani, et al.
Published: (2024)
Similar Items
-
Neural Optimizer Equation, Decay Function, and Learning Rate Schedule Joint Evolution
by: Morgan, Brandon, et al.
Published: (2024) -
All in one timestep: Enhancing Sparsity and Energy efficiency in Multi-level Spiking Neural Networks
by: Castagnetti, Andrea, et al.
Published: (2025) -
Exploiting Heterogeneity in Timescales for Sparse Recurrent Spiking Neural Networks for Energy-Efficient Edge Computing
by: Chakraborty, Biswadeep, et al.
Published: (2024) -
Spiker-LL: An Energy-Efficient FPGA Accelerator Enabling Adaptive Local Learning in Spiking Neural Networks
by: Caviglia, Alessio, et al.
Published: (2026) -
Energy Costs and Neural Complexity Evolution in Changing Environments
by: Heesom-Green, Sian, et al.
Published: (2025)