Copertina

Learning Long-Range Dependencies with Temporal Predictive Coding

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Potter, Tom, Rhodes, Oliver
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Learning Long Sequences in Spiking Neural Networks
di: Stan, Matei Ioan, et al.
Pubblicazione: (2023)

SpoT-Mamba: Learning Long-Range Dependency on Spatio-Temporal Graphs with Selective State Spaces
di: Choi, Jinhyeok, et al.
Pubblicazione: (2024)

Learning Long Range Dependencies on Graphs via Random Walks
di: Chen, Dexiong, et al.
Pubblicazione: (2024)

Evaluating Long Range Dependency Handling in Code Generation LLMs
di: Assogba, Yannick, et al.
Pubblicazione: (2024)

Predicting Price Movements in High-Frequency Financial Data with Spiking Neural Networks
di: Ezinwoke, Brian, et al.
Pubblicazione: (2025)

Sketch-Augmented Features Improve Learning Long-Range Dependencies in Graph Neural Networks
di: Hosseini, Ryien, et al.
Pubblicazione: (2025)

Multi-Window Temporal Analysis for Enhanced Arrhythmia Classification: Leveraging Long-Range Dependencies in Electrocardiogram Signals
di: Wang, Tiezhi, et al.
Pubblicazione: (2025)

On the Mirage of Long-Range Dependency, with an Application to Integer Multiplication
di: Wei, Zichao
Pubblicazione: (2026)

Analysis of Long Range Dependency Understanding in State Space Models
di: Ravikumar, Srividya, et al.
Pubblicazione: (2026)

Why Can't Transformers Learn Multiplication? Reverse-Engineering Reveals Long-Range Dependency Pitfalls
di: Bai, Xiaoyan, et al.
Pubblicazione: (2025)

BlockEcho: Retaining Long-Range Dependencies for Imputing Block-Wise Missing Data
di: Han, Qiao, et al.
Pubblicazione: (2024)

Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting
di: Kang, Bong Gyun, et al.
Pubblicazione: (2024)

ParallelTime: Dynamically Weighting the Balance of Short- and Long-Term Temporal Dependencies
di: Katav, Itay, et al.
Pubblicazione: (2025)

Modeling Temporal Dependencies within the Target for Long-Term Time Series Forecasting
di: Xiong, Qi, et al.
Pubblicazione: (2024)

Do Bayesian Neural Networks Improve Weapon System Predictive Maintenance?
di: Potter, Michael, et al.
Pubblicazione: (2023)

Provable Long-Range Benefits of Next-Token Prediction
di: Cao, Xinyuan, et al.
Pubblicazione: (2025)

Efficient Online Learning with Predictive Coding Networks: Exploiting Temporal Correlations
di: Zadeh-Jousdani, Darius Masoum, et al.
Pubblicazione: (2025)

Long Range Switching Time Series Prediction via State Space Model
di: Zhang, Jiaming, et al.
Pubblicazione: (2024)

Quantifying Memory Use in Reinforcement Learning with Temporal Range
di: Lafuente-Mercado, Rodney, et al.
Pubblicazione: (2025)

PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction
di: Jiang, Jiawei, et al.
Pubblicazione: (2023)

Hybrid Transformer and Spatial-Temporal Self-Supervised Learning for Long-term Traffic Prediction
di: Zhu, Wang, et al.
Pubblicazione: (2024)

Fast Polypharmacy Side Effect Prediction Using Tensor Factorisation
di: Lloyd, Oliver, et al.
Pubblicazione: (2024)

Temporal Predictive Coding for Gradient Compression in Distributed Learning
di: Edin, Adrian, et al.
Pubblicazione: (2024)

ExPairT-LLM: Exact Learning for LLM Code Selection by Pairwise Queries
di: Yuviler, Tom, et al.
Pubblicazione: (2025)

Dirac--Bianconi Graph Neural Networks -- Enabling Non-Diffusive Long-Range Graph Predictions
di: Nauck, Christian, et al.
Pubblicazione: (2024)

Machine-Learning Interatomic Potentials for Long-Range Systems
di: Ji, Yajie, et al.
Pubblicazione: (2025)

Efficient Learning of Long-Range and Equivariant Quantum Systems
di: Šmíd, Štěpán, et al.
Pubblicazione: (2023)

SineNet: Learning Temporal Dynamics in Time-Dependent Partial Differential Equations
di: Zhang, Xuan, et al.
Pubblicazione: (2024)

Multiscale Physics-Informed Neural Network for Complex Fluid Flows with Long-Range Dependencies
di: Kumar, Prashant, et al.
Pubblicazione: (2026)

SHARP: Sleep-based Hierarchical Accelerated Replay for Long Range Non-Stationary Temporal Pattern Recognition
di: Dey, Jayanta, et al.
Pubblicazione: (2026)

Capturing the Temporal Dependence of Training Data Influence
di: Wang, Jiachen T., et al.
Pubblicazione: (2024)

On the Identification of Temporally Causal Representation with Instantaneous Dependence
di: Li, Zijian, et al.
Pubblicazione: (2024)

Learn to Jump: Adaptive Random Walks for Long-Range Propagation through Graph Hierarchies
di: Mathys, Joël, et al.
Pubblicazione: (2025)

Heavy-Tailed and Long-Range Dependent Noise in Stochastic Approximation: A Finite-Time Analysis
di: Chandak, Siddharth, et al.
Pubblicazione: (2026)

ReciNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction
di: Nie, Jianan, et al.
Pubblicazione: (2025)

Transfer Learning for Temporal Link Prediction
di: Chatterjee, Ayan, et al.
Pubblicazione: (2025)

AdaGamma: State-Dependent Discounting for Temporal Adaptation in Reinforcement Learning
di: Wang, Yaomin, et al.
Pubblicazione: (2026)

Incremental Learning of Affordances using Markov Logic Networks
di: Potter, George, et al.
Pubblicazione: (2024)

Bridging Predictive Coding and MDL: A Two-Part Code Framework for Deep Learning
di: Prada, Benjamin, et al.
Pubblicazione: (2025)

Generalization of Long-Range Machine Learning Potentials in Complex Chemical Spaces
di: Sanocki, Michal, et al.
Pubblicazione: (2025)