Cover Image

HKT: A Biologically Inspired Framework for Modular Hereditary Knowledge Transfer in Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tchenko, Yanick Chistian, Mohr, Felix, Abdelkader, Hicham Hadj, Tabia, Hedi
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adaptive Pruning with Module Robustness Sensitivity: Balancing Compression and Robustness
by: Bai, Lincen, et al.
Published: (2024)

Representation learning from OCT images
by: Tabia, Hedi, et al.
Published: (2026)

The Unreasonable Effectiveness Of Early Discarding After One Epoch In Neural Network Hyperparameter Optimization
by: Egele, Romain, et al.
Published: (2024)

Multiple Additive Neural Networks for Structured and Unstructured Data
by: Mohr, Janis, et al.
Published: (2026)

Range, not Independence, Drives Modularity in Biologically Inspired Representations
by: Dorrell, Will, et al.
Published: (2024)

SortedNet: A Scalable and Generalized Framework for Training Modular Deep Neural Networks
by: Valipour, Mojtaba, et al.
Published: (2023)

DFReg: A Physics-Inspired Framework for Global Weight Distribution Regularization in Neural Networks
by: Ruggieri, Giovanni
Published: (2025)

One-Shot Identification with Different Neural Network Approaches
by: Mohr, Janis, et al.
Published: (2026)

Breaking Neural Network Scaling Laws with Modularity
by: Boopathy, Akhilan, et al.
Published: (2024)

NoEsis: Differentially Private Knowledge Transfer in Modular LLM Adaptation
by: Romijnders, Rob, et al.
Published: (2025)

Learning Curves for Decision Making in Supervised Machine Learning: A Survey
by: Mohr, Felix, et al.
Published: (2022)

PENEX: AdaBoost-Inspired Neural Network Regularization
by: Kladny, Klaus-Rudolf, et al.
Published: (2025)

Behavior-Inspired Neural Networks for Relational Inference
by: Yang, Yulong, et al.
Published: (2024)

Hypergraph Neural Diffusion: A PDE-Inspired Framework for Hypergraph Message Passing
by: Zhou, Zhiheng, et al.
Published: (2026)

HyperSBINN: A Hypernetwork-Enhanced Systems Biology-Informed Neural Network for Efficient Drug Cardiosafety Assessment
by: Soukarieh, Inass, et al.
Published: (2024)

Izhikevich-Inspired Temporal Dynamics for Enhancing Privacy, Efficiency, and Transferability in Spiking Neural Networks
by: Moshruba, Ayana, et al.
Published: (2025)

A Unified Framework for Knowledge Transfer in Bidirectional Model Scaling
by: Shen, Jianlu, et al.
Published: (2026)

Reservoir Computing: A New Paradigm for Neural Networks
by: Grezes, Felix
Published: (2025)

Bio-Inspired Artificial Neural Networks based on Predictive Coding
by: Casnici, Davide, et al.
Published: (2025)

On The Temporal Domain of Differential Equation Inspired Graph Neural Networks
by: Eliasof, Moshe, et al.
Published: (2024)

Studying Cross-cluster Modularity in Neural Networks
by: Golechha, Satvik, et al.
Published: (2025)

Training Neural Networks for Modularity aids Interpretability
by: Golechha, Satvik, et al.
Published: (2024)

Prefetching Cache Optimization Using Graph Neural Networks: A Modular Framework and Conceptual Analysis
by: Qowy, F. I.
Published: (2025)

Adversarial Vulnerability Transcends Computational Paradigms: Feature Engineering Provides No Defense Against Neural Adversarial Transfer
by: Hsain, Achraf, et al.
Published: (2026)

Tiny Neural Networks for Multi-Object Tracking in a Modular Kalman Framework
by: Holz, Christian Alexander, et al.
Published: (2025)

Investigating Plausibility of Biologically Inspired Bayesian Learning in ANNs
by: Zaveri, Ram
Published: (2024)

Modular Boundaries in Recurrent Neural Networks
by: Tanner, Jacob, et al.
Published: (2023)

Physics-Inspired Binary Neural Networks: Interpretable Compression with Theoretical Guarantees
by: Eamaz, Arian, et al.
Published: (2025)

LCDB 1.1: A Database Illustrating Learning Curves Are More Ill-Behaved Than Previously Thought
by: Yan, Cheng, et al.
Published: (2025)

VECTOR: Velocity-Enhanced GRU Neural Network for Real-Time 3D UAV Trajectory Prediction
by: Nacar, Omer, et al.
Published: (2024)

Graph Neural Networks for Temperature-Dependent Activity Coefficient Prediction of Solutes in Ionic Liquids
by: Rittig, Jan G., et al.
Published: (2022)

Graph Neural Network-Based Reinforcement Learning for Controlling Biological Networks - the GATTACA Framework
by: Mizera, Andrzej, et al.
Published: (2025)

Physics-Informed Neural Network Frameworks for the Analysis of Engineering and Biological Dynamical Systems Governed by Ordinary Differential Equations
by: Whitman, Tyrus, et al.
Published: (2025)

Spark: Modular Spiking Neural Networks
by: Franco, Mario, et al.
Published: (2026)

NeuroPlastic: A Plasticity-Modulated Optimizer for Biologically Inspired Learning Dynamics
by: Jiang, Douglas, et al.
Published: (2026)

Fourier Circuits in Neural Networks and Transformers: A Case Study of Modular Arithmetic with Multiple Inputs
by: Li, Chenyang, et al.
Published: (2024)

Representation-Aware Distributionally Robust Optimization: A Knowledge Transfer Framework
by: Wang, Zitao, et al.
Published: (2025)

A Probabilistic Framework for Modular Continual Learning
by: Valkov, Lazar, et al.
Published: (2023)

Credal Prediction based on Relative Likelihood
by: Löhr, Timo, et al.
Published: (2025)

Learning Greens Operators through Hierarchical Neural Networks Inspired by the Fast Multipole Method
by: Fognini, Emilio McAllister, et al.
Published: (2025)