Imagen de Portada

Deep Learning and Transfer Learning Architectures for English Premier League Player Performance Forecasting

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Frees, Daniel, Ravella, Pranav, Zhang, Charlie
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning 68T07
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning
por: Bastounis, Alexander, et al.
Publicado: (2023)

Learning Latent Spaces for Domain Generalization in Time Series Forecasting
por: Deng, Songgaojun, et al.
Publicado: (2024)

Cooperative Multi-Agent Deep Reinforcement Learning in Content Ranking Optimization
por: Qin, Zhou, et al.
Publicado: (2024)

A Generalization Bound for a Family of Implicit Networks
por: Fung, Samy Wu, et al.
Publicado: (2024)

Multi-modal Transfer Learning between Biological Foundation Models
por: Garau-Luis, Juan Jose, et al.
Publicado: (2024)

Deep Learning for Hydroelectric Optimization: Generating Long-Term River Discharge Scenarios with Ensemble Forecasts from Global Circulation Models
por: Dias, Julio Alberto Silva
Publicado: (2024)

ASNN: Learning to Suggest Neural Architectures from Performance Distributions
por: Hong, Jinwook
Publicado: (2025)

Towards Optimal Convolutional Transfer Learning Architectures for Breast Lesion Classification and ACL Tear Detection
por: Frees, Daniel, et al.
Publicado: (2025)

A Comprehensive View of Personalized Federated Learning on Heterogeneous Clinical Datasets
por: Tavakoli, Fatemeh, et al.
Publicado: (2023)

Feature Learning Beyond the Edge of Stability
por: Terjék, Dávid
Publicado: (2025)

Markov Chain Estimation with In-Context Learning
por: Lepage, Simon, et al.
Publicado: (2025)

Chebyshev-Augmented One-Shot Transfer Learning for PINNs on Nonlinear Differential Equations
por: Rao, Yiqi, et al.
Publicado: (2026)

BP(λ): Online Learning via Synthetic Gradients
por: Pemberton, Joseph, et al.
Publicado: (2024)

Closed-Form Feedback-Free Learning with Forward Projection
por: O'Shea, Robert, et al.
Publicado: (2025)

Wave-Attractor-Tree: A Hierarchical Binary Tree Reduction Architecture for Efficient Sequence Modeling
por: Berezkin, Igor
Publicado: (2026)

A Teacher-Student Perspective on the Dynamics of Learning Near the Optimal Point
por: Couto, Carlos, et al.
Publicado: (2025)

Tadpole: Autoencoders as Foundation Models for 3D PDEs with Online Learning
por: Liu, Qiang, et al.
Publicado: (2026)

Temporal Attention Evolutional Graph Convolutional Network for Multivariate Time Series Forecasting
por: Zhao, Xinlong, et al.
Publicado: (2025)

Deep generative models as the probability transformation functions
por: Bondar, Vitalii, et al.
Publicado: (2025)

Structured Knowledge Accumulation: The Principle of Entropic Least Action in Forward-Only Neural Learning
por: Quantiota, Bouarfa Mahi
Publicado: (2025)

A Hybrid Deep Learning and Anomaly Detection Framework for Real-Time Malicious URL Classification
por: Khaled, Berkani, et al.
Publicado: (2025)

Teaching and Learning under Deductive Errors
por: Telle, Jan Arne, et al.
Publicado: (2026)

Training-Free Generative Sampling via Moment-Matched Score Smoothing
por: Yao, Zhenyu, et al.
Publicado: (2026)

Transfer Learning through Enhanced Sufficient Representation: Enriching Source Domain Knowledge with Target Data
por: Ge, Yeheng, et al.
Publicado: (2025)

Exploring Efficient Learning of Small BERT Networks with LoRA and DoRA
por: Frees, Daniel, et al.
Publicado: (2025)

Learning to Control the Smoothness of Graph Convolutional Network Features
por: Wang, Shih-Hsin, et al.
Publicado: (2024)

Feature Selection with Annealing for Forecasting Financial Time Series
por: Pabuccu, Hakan, et al.
Publicado: (2023)

Towards Understanding the Link Between Modularity and Performance in Neural Networks for Reinforcement Learning
por: Munn, Humphrey, et al.
Publicado: (2022)

Fairness-Aware Federated Learning with Trajectory Shapley Value
por: Kuznetsov, Daniel, et al.
Publicado: (2026)

Autoencoded UMAP-Enhanced Clustering for Unsupervised Learning
por: Chavooshi, Malihehsadat, et al.
Publicado: (2025)

From Features to Graphs: Exploring Graph Structures and Pairwise Interactions via GNNs
por: Yamchote, Phaphontee, et al.
Publicado: (2025)

Influence-Inspired Spectral Rotations for Extreme Low-Bit LLM Quantization
por: Pavlov, Gorgi
Publicado: (2026)

Deep learning the Hurst parameter of linear fractional processes and assessing its reliability
por: Boros, Dániel, et al.
Publicado: (2024)

Attention to Mamba: A Recipe for Cross-Architecture Distillation
por: Moudgil, Abhinav, et al.
Publicado: (2026)

Deep Learning-Based Forecasting of Boarding Patient Counts to Address ED Overcrowding
por: Vural, Orhun, et al.
Publicado: (2025)

The Inhibitor: ReLU and Addition-Based Attention for Efficient Transformers under Fully Homomorphic Encryption on the Torus
por: Brännvall, Rickard, et al.
Publicado: (2023)

Forecasting Nigerian Equity Stock Returns Using Long Short-Term Memory Technique
por: Ojo, Adebola K., et al.
Publicado: (2025)

Neuro-Spectral Architectures for Causal Physics-Informed Networks
por: Bizzi, Arthur, et al.
Publicado: (2025)

Enhancing Predictive Accuracy in Tennis: Integrating Fuzzy Logic and CV-GRNN for Dynamic Match Outcome and Player Momentum Analysis
por: Li, Kechen, et al.
Publicado: (2025)

SEAL: Searching Expandable Architectures for Incremental Learning
por: Gambella, Matteo, et al.
Publicado: (2025)