Saved in:
| Main Authors: | Cheon, Jeonghwan, Lee, Sang Wan, Paik, Se-Bum |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2405.16731 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Pretraining with random noise for uncertainty calibration
by: Cheon, Jeonghwan, et al.
Published: (2024)
by: Cheon, Jeonghwan, et al.
Published: (2024)
Neuromimetic metaplasticity for adaptive continual learning
by: Cho, Suhee, et al.
Published: (2024)
by: Cho, Suhee, et al.
Published: (2024)
One-Time Soft Alignment Enables Resilient Learning without Weight Transport
by: Cheon, Jeonghwan, et al.
Published: (2025)
by: Cheon, Jeonghwan, et al.
Published: (2025)
Expressivity of Neural Networks with Random Weights and Learned Biases
by: Williams, Ezekiel, et al.
Published: (2024)
by: Williams, Ezekiel, et al.
Published: (2024)
Learning to Forget: Continual Learning with Adaptive Weight Decay
by: Ramesh, Aditya A., et al.
Published: (2026)
by: Ramesh, Aditya A., et al.
Published: (2026)
Reservoir Computing via Multi-Scale Random Fourier Features for Forecasting Fast-Slow Dynamical Systems
by: Laha, S. K.
Published: (2025)
by: Laha, S. K.
Published: (2025)
R-FORCE: Robust Learning for Random Recurrent Neural Networks
by: Zheng, Yang, et al.
Published: (2020)
by: Zheng, Yang, et al.
Published: (2020)
Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs
by: Frasca, Fabrizio, et al.
Published: (2024)
by: Frasca, Fabrizio, et al.
Published: (2024)
Learning Self-Growth Maps for Fast and Accurate Imbalanced Streaming Data Clustering
by: Zhang, Yiqun, et al.
Published: (2024)
by: Zhang, Yiqun, et al.
Published: (2024)
Supervised Spike Agreement Dependent Plasticity for Fast Local Learning in Spiking Neural Networks
by: S, Gouri Lakshmi, et al.
Published: (2026)
by: S, Gouri Lakshmi, et al.
Published: (2026)
Recursive Dynamics in Fast-Weights Homeostatic Reentry Networks: Toward Reflective Intelligence
by: Chae, B. G.
Published: (2025)
by: Chae, B. G.
Published: (2025)
Recurrent Complex-Weighted Autoencoders for Unsupervised Object Discovery
by: Gopalakrishnan, Anand, et al.
Published: (2024)
by: Gopalakrishnan, Anand, et al.
Published: (2024)
Looped Transformers are Better at Learning Learning Algorithms
by: Yang, Liu, et al.
Published: (2023)
by: Yang, Liu, et al.
Published: (2023)
Gated Recurrent Neural Networks with Weighted Time-Delay Feedback
by: Erichson, N. Benjamin, et al.
Published: (2022)
by: Erichson, N. Benjamin, et al.
Published: (2022)
Stable and Robust Deep Learning By Hyperbolic Tangent Exponential Linear Unit (TeLU)
by: Fernandez, Alfredo, et al.
Published: (2024)
by: Fernandez, Alfredo, et al.
Published: (2024)
Bio-Inspired Adaptive Neurons for Dynamic Weighting in Artificial Neural Networks
by: Islam, Ashhadul, et al.
Published: (2024)
by: Islam, Ashhadul, et al.
Published: (2024)
Should Under-parameterized Student Networks Copy or Average Teacher Weights?
by: Şimşek, Berfin, et al.
Published: (2023)
by: Şimşek, Berfin, et al.
Published: (2023)
Walking the Weight Manifold: a Topological Approach to Conditioning Inspired by Neuromodulation
by: Benjamin, Ari S., et al.
Published: (2025)
by: Benjamin, Ari S., et al.
Published: (2025)
Improving Language Plasticity via Pretraining with Active Forgetting
by: Chen, Yihong, et al.
Published: (2023)
by: Chen, Yihong, et al.
Published: (2023)
Randomly Weighted Neuromodulation in Neural Networks Facilitates Learning of Manifolds Common Across Tasks
by: Hong, Jinyung, et al.
Published: (2023)
by: Hong, Jinyung, et al.
Published: (2023)
Spiking Neural Networks with Random Network Architecture
by: Dai, Zihan, et al.
Published: (2025)
by: Dai, Zihan, et al.
Published: (2025)
Linearly Constrained Weights: Reducing Activation Shift for Faster Training of Neural Networks
by: Kutsuna, Takuro
Published: (2024)
by: Kutsuna, Takuro
Published: (2024)
Dynamically Weighted Momentum with Adaptive Step Sizes for Efficient Deep Network Training
by: Wang, Zhifeng, et al.
Published: (2025)
by: Wang, Zhifeng, et al.
Published: (2025)
Fast gradient-free activation maximization for neurons in spiking neural networks
by: Pospelov, Nikita, et al.
Published: (2023)
by: Pospelov, Nikita, et al.
Published: (2023)
A Self-Ensemble Inspired Approach for Effective Training of Binary-Weight Spiking Neural Networks
by: Meng, Qingyan, et al.
Published: (2025)
by: Meng, Qingyan, et al.
Published: (2025)
Generalized Dynamic Brain Functional Connectivity Based on Random Convolutions
by: Duan, Yongjie, et al.
Published: (2024)
by: Duan, Yongjie, et al.
Published: (2024)
ART: Actually Robust Training
by: Chwilczyński, Sebastian, et al.
Published: (2024)
by: Chwilczyński, Sebastian, et al.
Published: (2024)
D-Score: A Synapse-Inspired Approach for Filter Pruning
by: Park, Doyoung, et al.
Published: (2023)
by: Park, Doyoung, et al.
Published: (2023)
The Alpha-Alternator: Dynamic Adaptation To Varying Noise Levels In Sequences Using The Vendi Score For Improved Robustness and Performance
by: Rezaei, Mohammad Reza, et al.
Published: (2025)
by: Rezaei, Mohammad Reza, et al.
Published: (2025)
Improved Robustness and Hyperparameter Selection in the Dense Associative Memory
by: McAlister, Hayden, et al.
Published: (2024)
by: McAlister, Hayden, et al.
Published: (2024)
Neuroformer: Multimodal and Multitask Generative Pretraining for Brain Data
by: Antoniades, Antonis, et al.
Published: (2023)
by: Antoniades, Antonis, et al.
Published: (2023)
Convex-Neural RRT*: Fast and Reliable Learning-Guided Sampling for High-Quality Robot Path Planning
by: Cheriet, Hichem, et al.
Published: (2026)
by: Cheriet, Hichem, et al.
Published: (2026)
Real-time Noise Detection and Classification in Single-Channel EEG: A Lightweight Machine Learning Approach for EMG, White Noise, and EOG Artifacts
by: Enshaei, Hossein, et al.
Published: (2025)
by: Enshaei, Hossein, et al.
Published: (2025)
Scalable Learning in Structured Recurrent Spiking Neural Networks without Backpropagation
by: Tang, Bo, et al.
Published: (2026)
by: Tang, Bo, et al.
Published: (2026)
Mirror Descent Policy Optimisation for Robust Constrained Markov Decision Processes
by: Bossens, David M., et al.
Published: (2025)
by: Bossens, David M., et al.
Published: (2025)
Robust MAE-Driven NAS: From Mask Reconstruction to Architecture Innovation
by: Hu, Yiming, et al.
Published: (2023)
by: Hu, Yiming, et al.
Published: (2023)
A Little Rank Goes a Long Way: Random Scaffolds with LoRA Adapters Are All You Need
by: Hazan, Hananel, et al.
Published: (2026)
by: Hazan, Hananel, et al.
Published: (2026)
Cultivating Archipelago of Forests: Evolving Robust Decision Trees through Island Coevolution
by: Żychowski, Adam, et al.
Published: (2024)
by: Żychowski, Adam, et al.
Published: (2024)
Blending Optimal Control and Biologically Plausible Learning for Noise-Robust Physical Neural Networks
by: Sunada, Satoshi, et al.
Published: (2025)
by: Sunada, Satoshi, et al.
Published: (2025)
Effects of structural properties of neural networks on machine learning performance
by: Arya, Yash, et al.
Published: (2025)
by: Arya, Yash, et al.
Published: (2025)
Similar Items
-
Pretraining with random noise for uncertainty calibration
by: Cheon, Jeonghwan, et al.
Published: (2024) -
Neuromimetic metaplasticity for adaptive continual learning
by: Cho, Suhee, et al.
Published: (2024) -
One-Time Soft Alignment Enables Resilient Learning without Weight Transport
by: Cheon, Jeonghwan, et al.
Published: (2025) -
Expressivity of Neural Networks with Random Weights and Learned Biases
by: Williams, Ezekiel, et al.
Published: (2024) -
Learning to Forget: Continual Learning with Adaptive Weight Decay
by: Ramesh, Aditya A., et al.
Published: (2026)