Cover Image

Memory Networks: Towards Fully Biologically Plausible Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ruiz, Jacobo, Gupta, Manas
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Neural and Evolutionary Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning
by: Kao, Chia-Hsiang, et al.
Published: (2024)

Multiscale Astrocyte Network Calcium Dynamics for Biologically Plausible Intelligence in Anomaly Detection
by: Iskar, Berk, et al.
Published: (2025)

Towards Physical Plausibility in Neuroevolution Systems
by: Cortês, Gabriel, et al.
Published: (2024)

Fully Spiking Actor Network with Intra-layer Connections for Reinforcement Learning
by: Chen, Ding, et al.
Published: (2024)

A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks
by: Salvatori, Tommaso, et al.
Published: (2022)

Graph Memory Learning: Imitating Lifelong Remembering and Forgetting of Brain Networks
by: Miao, Jiaxing, et al.
Published: (2024)

Learning Successor Features with Distributed Hebbian Temporal Memory
by: Dzhivelikian, Evgenii, et al.
Published: (2023)

CLASSP: a Biologically-Inspired Approach to Continual Learning through Adjustment Suppression and Sparsity Promotion
by: Ludwig, Oswaldo
Published: (2024)

Towards White Box Deep Learning
by: Satkiewicz, Maciej
Published: (2024)

Memory Mosaics
by: Zhang, Jianyu, et al.
Published: (2024)

Biologically Plausible Training of Deep Neural Networks Using a Top-down Credit Assignment Network
by: Chen, Jian-Hui, et al.
Published: (2022)

Toward Efficient Deep Spiking Neuron Networks:A Survey On Compression
by: Xie, Hui, et al.
Published: (2024)

Towards evolution of Deep Neural Networks through contrastive Self-Supervised learning
by: Vinhas, Adriano, et al.
Published: (2024)

Recursive Dynamics in Fast-Weights Homeostatic Reentry Networks: Toward Reflective Intelligence
by: Chae, B. G.
Published: (2025)

Toward End-to-End Bearing Fault Diagnosis for Industrial Scenarios with Spiking Neural Networks
by: Zuo, Lin, et al.
Published: (2024)

Learning Random Numbers to Realize Appendable Memory System for Artificial Intelligence to Acquire New Knowledge after Deployment
by: Yamada, Kazunori D
Published: (2024)

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

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

Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes
by: Hu, Jerry Yao-Chieh, et al.
Published: (2024)

Position: Biology is the Challenge Physics-Informed ML Needs to Evolve
by: Martinelli, Julien
Published: (2025)

Learning Heuristics for Transit Network Design and Improvement with Deep Reinforcement Learning
by: Holliday, Andrew, et al.
Published: (2024)

Half-Space Feature Learning in Neural Networks
by: Yadav, Mahesh Lorik, et al.
Published: (2024)

Mechanistic Neural Networks for Scientific Machine Learning
by: Pervez, Adeel, et al.
Published: (2024)

Introduction to Predictive Coding Networks for Machine Learning
by: Stenlund, Mikko
Published: (2025)

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

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

Learning Sequence Attractors in Recurrent Networks with Hidden Neurons
by: Lu, Yao, et al.
Published: (2024)

Meta-Learning Loss Functions for Deep Neural Networks
by: Raymond, Christian
Published: (2024)

Training Neural Networks with Optimal Double-Bayesian Learning
by: Bui, Vy, et al.
Published: (2026)

Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
by: Tan, Rong-Xi, et al.
Published: (2025)

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

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

Fast PINN Eigensolvers via Biconvex Reformulation
by: Banderwaar, Akshay Sai, et al.
Published: (2025)

Long-Sequence Memory with Temporal Kernels and Dense Hopfield Functionals
by: Farooq, Ahmed
Published: (2025)

Modality-Dependent Memory Mechanisms in Cross-Modal Neuromorphic Computing
by: Blessing, Effiong, et al.
Published: (2025)

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

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

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

Evolutionary Developmental Biology Can Serve as the Conceptual Foundation for a New Design Paradigm in Artificial Intelligence
by: Erden, Zeki Doruk, et al.
Published: (2025)

MTSpark: Enabling Multi-Task Learning with Spiking Neural Networks for Generalist Agents
by: Devkota, Avaneesh, et al.
Published: (2024)