Connectome-Guided Automatic Learning Rates for Deep Networks
Fuente:
arXiv
Saved in:
| Main Authors: | He, Peilin, Songdechakraiwut, Tananun |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Data-Efficient Neural Training with Dynamic Connectomes
by: Wu, Yutong, et al.
Published: (2025)
by: Wu, Yutong, et al.
Published: (2025)
Functional Connectivity Graph Neural Networks
by: Li, Yang, et al.
Published: (2025)
by: Li, Yang, et al.
Published: (2025)
Functional connectomes of neural networks
by: Songdechakraiwut, Tananun, et al.
Published: (2024)
by: Songdechakraiwut, Tananun, et al.
Published: (2024)
BioNIC: Biologically Inspired Neural Network for Image Classification Using Connectomics Principles
by: Prasanth, Diya, et al.
Published: (2026)
by: Prasanth, Diya, et al.
Published: (2026)
A Hierarchical Importance-Guided Multi-objective Evolutionary Framework for Deep Neural Network Pruning
by: Khan, Zak, et al.
Published: (2026)
by: Khan, Zak, et al.
Published: (2026)
Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help
by: Han, Keqi, et al.
Published: (2025)
by: Han, Keqi, et al.
Published: (2025)
Neuromorphic Simulation of Drosophila Melanogaster Brain Connectome on Loihi 2
by: Wang, Felix, et al.
Published: (2025)
by: Wang, Felix, et al.
Published: (2025)
BKDSNN: Enhancing the Performance of Learning-based Spiking Neural Networks Training with Blurred Knowledge Distillation
by: Xu, Zekai, et al.
Published: (2024)
by: Xu, Zekai, et al.
Published: (2024)
Integrating Pruning with Quantization for Efficient Deep Neural Networks Compression
by: Makenali, Sara, et al.
Published: (2025)
by: Makenali, Sara, et al.
Published: (2025)
Competition-based Adaptive ReLU for Deep Neural Networks
by: Chen, Junjia, et al.
Published: (2024)
by: Chen, Junjia, et al.
Published: (2024)
Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation
by: Yu, Chengting, et al.
Published: (2024)
by: Yu, Chengting, et al.
Published: (2024)
Annotated History of Modern AI and Deep Learning
by: Schmidhuber, Juergen
Published: (2022)
by: Schmidhuber, Juergen
Published: (2022)
Training Deep Normalization-Free Spiking Neural Networks with Lateral Inhibition
by: Liu, Peiyu, et al.
Published: (2025)
by: Liu, Peiyu, et al.
Published: (2025)
Stitching for Neuroevolution: Recombining Deep Neural Networks without Breaking Them
by: Guijt, Arthur, et al.
Published: (2024)
by: Guijt, Arthur, et al.
Published: (2024)
Evaluating Deep Neural Networks in Deployment (A Comparative and Replicability Study)
by: Pinconschi, Eduard, et al.
Published: (2024)
by: Pinconschi, Eduard, et al.
Published: (2024)
Evolutionary Optimization of Deep Learning Agents for Sparrow Mahjong
by: O'Connor, Jim, et al.
Published: (2025)
by: O'Connor, Jim, et al.
Published: (2025)
Deep Learning: Our Miraculous Year 1990-1991
by: Schmidhuber, Juergen
Published: (2020)
by: Schmidhuber, Juergen
Published: (2020)
Scalable Dendritic Modeling Advances Expressive and Robust Deep Spiking Neural Networks
by: Huang, Yifan, et al.
Published: (2024)
by: Huang, Yifan, et al.
Published: (2024)
Automatic Design of Optimization Test Problems with Large Language Models
by: Achtelik, Wojciech, et al.
Published: (2026)
by: Achtelik, Wojciech, et al.
Published: (2026)
Optimizing Spatio-Temporal Information Processing in Spiking Neural Networks via Unconstrained Leaky Integrate-and-Fire Neurons and Hybrid Coding
by: He, Huaxu
Published: (2024)
by: He, Huaxu
Published: (2024)
Surrogate-Assisted Evolution for Efficient Multi-branch Connection Design in Deep Neural Networks
by: Stapleton, Fergal, et al.
Published: (2025)
by: Stapleton, Fergal, et al.
Published: (2025)
A Latency Coding Framework for Deep Spiking Neural Networks with Ultra-Low Latency
by: Lu, Yi, et al.
Published: (2026)
by: Lu, Yi, et al.
Published: (2026)
CALM: Co-evolution of Algorithms and Language Model for Automatic Heuristic Design
by: Huang, Ziyao, et al.
Published: (2025)
by: Huang, Ziyao, et al.
Published: (2025)
A GPU Implementation of Multi-Guiding Spark Fireworks Algorithm for Efficient Black-Box Neural Network Optimization
by: Meng, Xiangrui, et al.
Published: (2025)
by: Meng, Xiangrui, et al.
Published: (2025)
Effective Adaptive Mutation Rates for Program Synthesis
by: Ni, Andrew, et al.
Published: (2024)
by: Ni, Andrew, et al.
Published: (2024)
Direct Training High-Performance Deep Spiking Neural Networks: A Review of Theories and Methods
by: Zhou, Chenlin, et al.
Published: (2024)
by: Zhou, Chenlin, et al.
Published: (2024)
A High-Throughput Spiking Neural Network Processor Enabling Synaptic Delay Emulation
by: Chen, Faquan, et al.
Published: (2025)
by: Chen, Faquan, et al.
Published: (2025)
Learning the Plasticity: Plasticity-Driven Learning Framework in Spiking Neural Networks
by: Shen, Guobin, et al.
Published: (2023)
by: Shen, Guobin, et al.
Published: (2023)
Deep Neural Network-guided PSO for Tracking a Global Optimal Position in Complex Dynamic Environment
by: Raharja, Stephen, et al.
Published: (2026)
by: Raharja, Stephen, et al.
Published: (2026)
Deep Reinforcement Learning-Assisted Automated Operator Portfolio for Constrained Multi-objective Optimization
by: Shao, Shuai, et al.
Published: (2026)
by: Shao, Shuai, et al.
Published: (2026)
Spatio-Temporal Decoupled Learning for Spiking Neural Networks
by: Ma, Chenxiang, et al.
Published: (2025)
by: Ma, Chenxiang, et al.
Published: (2025)
A Flexible Evolutionary Algorithm With Dynamic Mutation Rate Archive
by: Krejca, Martin S., et al.
Published: (2024)
by: Krejca, Martin S., et al.
Published: (2024)
All Constant Mutation Rates for the $(1+1)$ Evolutionary Algorithm
by: Kelley, Andrew James
Published: (2026)
by: Kelley, Andrew James
Published: (2026)
Spiking Neural Networks with Consistent Mapping Relations Allow High-Accuracy Inference
by: Li, Yang, et al.
Published: (2024)
by: Li, Yang, et al.
Published: (2024)
Efficient Parallel Training Methods for Spiking Neural Networks with Constant Time Complexity
by: Feng, Wanjin, et al.
Published: (2025)
by: Feng, Wanjin, et al.
Published: (2025)
Efficient Event-based Delay Learning in Spiking Neural Networks
by: Mészáros, Balázs, et al.
Published: (2025)
by: Mészáros, Balázs, et al.
Published: (2025)
Combining Convolution and Delay Learning in Recurrent Spiking Neural Networks
by: Zebendo, Lúcio Folly Sanches, et al.
Published: (2026)
by: Zebendo, Lúcio Folly Sanches, et al.
Published: (2026)
Efficient Online Learning for Networks of Two-Compartment Spiking Neurons
by: Yin, Yujia, et al.
Published: (2024)
by: Yin, Yujia, et al.
Published: (2024)
All Mutation Rates $c/n$ for the $(1+1)$ Evolutionary Algorithm
by: Kelley, Andrew James
Published: (2026)
by: Kelley, Andrew James
Published: (2026)
Parallel Spiking Unit for Efficient Training of Spiking Neural Networks
by: Li, Yang, et al.
Published: (2024)
by: Li, Yang, et al.
Published: (2024)
Similar Items
-
Data-Efficient Neural Training with Dynamic Connectomes
by: Wu, Yutong, et al.
Published: (2025) -
Functional Connectivity Graph Neural Networks
by: Li, Yang, et al.
Published: (2025) -
Functional connectomes of neural networks
by: Songdechakraiwut, Tananun, et al.
Published: (2024) -
BioNIC: Biologically Inspired Neural Network for Image Classification Using Connectomics Principles
by: Prasanth, Diya, et al.
Published: (2026) -
A Hierarchical Importance-Guided Multi-objective Evolutionary Framework for Deep Neural Network Pruning
by: Khan, Zak, et al.
Published: (2026)