Copertina

Tuning the Weights: The Impact of Initial Matrix Configurations on Successor Features Learning Efficacy

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Lee, Hyunsu
Natura:	Preprint
Pubblicazione:	2021
Soggetti:	Neurons and Cognition Neural and Evolutionary Computing
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

The Influence of Initial Connectivity on Biologically Plausible Learning
di: Liu, Weixuan, et al.
Pubblicazione: (2024)

A Practical Guide to Tuning Spiking Neuronal Dynamics
di: Gebhardt, William, et al.
Pubblicazione: (2025)

Coin-Flipping In The Brain: Statistical Learning with Neuronal Assemblies
di: Dabagia, Max, et al.
Pubblicazione: (2024)

Smooth Exact Gradient Descent Learning in Spiking Neural Networks
di: Klos, Christian, et al.
Pubblicazione: (2023)

Time-Evolving Dynamical System for Learning Latent Representations of Mouse Visual Neural Activity
di: Huang, Liwei, et al.
Pubblicazione: (2024)

Biologically-Plausible Topology Improved Spiking Actor Network for Efficient Deep Reinforcement Learning
di: Zhang, Duzhen, et al.
Pubblicazione: (2024)

Expressivity of Neural Networks with Random Weights and Learned Biases
di: Williams, Ezekiel, et al.
Pubblicazione: (2024)

Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations
di: Stoewer, Paul, et al.
Pubblicazione: (2023)

One-shot learning of paired association navigation with biologically plausible schemas
di: Kumar, M Ganesh, et al.
Pubblicazione: (2021)

Teaching signal synchronization in deep neural networks with prospective neurons
di: Zucchet, Nicoas, et al.
Pubblicazione: (2025)

On Broken Symmetry in Cognition
di: Li, Xin
Pubblicazione: (2023)

Building functional and mechanistic models of cortical computation based on canonical cell type connectivity
di: Granier, Arno, et al.
Pubblicazione: (2025)

"What" x "When" working memory representations using Laplace Neural Manifolds
di: Sarkar, Aakash, et al.
Pubblicazione: (2024)

Analysis of a Spatialized Brain-Body-Environment System
di: Pak, Denizhan, et al.
Pubblicazione: (2025)

The generalized Hierarchical Gaussian Filter
di: Weber, Lilian Aline, et al.
Pubblicazione: (2023)

Exploring the role of structure in a time constrained decision task
di: Chaix-Eichel, Naomi, et al.
Pubblicazione: (2024)

Von Economo neurons enable reliable social skill acquisition in recurrent spiking neural networks: a computational account with clinical predictions
di: Keskin, Esila
Pubblicazione: (2026)

A Unified Phase-native Computational Principle Governs Hippocampal Spike Timing and Neural Coding
di: Ahmadvand, Reza, et al.
Pubblicazione: (2026)

Reply to: Limitations in odour recognition and generalisation in a neuromorphic olfactory circuit
di: Moyal, Roy, et al.
Pubblicazione: (2024)

A Spatiotemporal Perspective on Dynamical Computation in Neural Information Processing Systems
di: Keller, T. Anderson, et al.
Pubblicazione: (2024)

Regime Mapping of Oscillatory States in Balanced Spiking Networks with Multiple Time Scales
di: Kuo, Tsung-Han, et al.
Pubblicazione: (2026)

Canonical Functionalism: Defining Functional Structure without Observer-Relative Semantic Maps
di: Kanai, Ryota, et al.
Pubblicazione: (2026)

BrainFuse: a unified infrastructure integrating realistic biological modeling and core AI methodology
di: Chen, Baiyu, et al.
Pubblicazione: (2026)

Spatial Spiking Neural Networks Enable Efficient and Robust Temporal Computation
di: Landsmeer, Lennart P. L., et al.
Pubblicazione: (2025)

Heterogeneous quantization regularizes spiking neural network activity
di: Moyal, Roy, et al.
Pubblicazione: (2024)

Evolving choice hysteresis in reinforcement learning: comparing the adaptive value of positivity bias and gradual perseveration
di: Hoxha, Isabelle, et al.
Pubblicazione: (2024)

Designing an adaptive room for captivating the collective consciousness from internal states
di: Flores-Ramírez, Adán, et al.
Pubblicazione: (2024)

Neural Computation Without Slots: Steps Towards Biologically Plausible Memory and Attention in Natural and Artificial Intelligence
di: Bhandarkar, Shaunak, et al.
Pubblicazione: (2025)

Event-driven eligibility propagation in large sparse networks: efficiency shaped by biological realism
di: Korcsak-Gorzo, Agnes, et al.
Pubblicazione: (2025)

Discovering alternative solutions beyond the simplicity bias in recurrent neural networks
di: Qian, William, et al.
Pubblicazione: (2025)

A Computational Framework for Modeling Emergence of Color Vision in the Human Brain
di: Kotani, Atsunobu, et al.
Pubblicazione: (2024)

Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli
di: Huang, Liwei, et al.
Pubblicazione: (2023)

Emergence of robust looming selectivity via coordinated inhibitory neural computations
di: Fu, Qinbing, et al.
Pubblicazione: (2025)

Nonlinear Neural Dynamics and Classification Accuracy in Reservoir Computing
di: Metzner, Claus, et al.
Pubblicazione: (2024)

Bridging Brains and Machines: A Unified Frontier in Neuroscience, Artificial Intelligence, and Neuromorphic Systems
di: Shankar, Sohan, et al.
Pubblicazione: (2025)

The Role of Excitatory Parvalbumin-positive Neurons in the Tectofugal Pathway of Pigeon (Columba livia) Hierarchical Visual Processing
di: Lu, Shan, et al.
Pubblicazione: (2025)

Recombinant dynamical systems
di: Kato, Saul
Pubblicazione: (2025)

Lu.i -- A low-cost electronic neuron for education and outreach
di: Stradmann, Yannik, et al.
Pubblicazione: (2024)

Unsupervised representation learning with Hebbian synaptic and structural plasticity in brain-like feedforward neural networks
di: Ravichandran, Naresh, et al.
Pubblicazione: (2024)

A Portable Solution for Simultaneous Human Movement and Mobile EEG Acquisition: Readiness Potentials for Basketball Free-throw Shooting
di: Contreras-Altamirano, Miguel, et al.
Pubblicazione: (2025)