Gaining Momentum: Uncovering Hidden Scoring Dynamics in Hockey through Deep Neural Sequencing and Causal Modeling
Fuente:
arXiv
Saved in:
| Main Authors: | Griffiths, Daniel, Moskow, Piper |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Learning to Play Air Hockey with Model-Based Deep Reinforcement Learning
by: Orsula, Andrej
Published: (2024)
by: Orsula, Andrej
Published: (2024)
Uncovering Causal Relation Shifts in Event Sequences under Out-of-Domain Interventions
by: Zinat, Kazi Tasnim, et al.
Published: (2025)
by: Zinat, Kazi Tasnim, et al.
Published: (2025)
Score-based Generative Models with Adaptive Momentum
by: Wen, Ziqing, et al.
Published: (2024)
by: Wen, Ziqing, et al.
Published: (2024)
Uncovering Hidden Systematics in Neural Network Models for High Energy Physics
by: Flek, Lucie, et al.
Published: (2026)
by: Flek, Lucie, et al.
Published: (2026)
Uncovering the Hidden Cost of Model Compression
by: Misra, Diganta, et al.
Published: (2023)
by: Misra, Diganta, et al.
Published: (2023)
Towards Empowerment Gain through Causal Structure Learning in Model-Based RL
by: Cao, Hongye, et al.
Published: (2025)
by: Cao, Hongye, et al.
Published: (2025)
Neural Score Matching for High-Dimensional Causal Inference
by: Clivio, Oscar, et al.
Published: (2022)
by: Clivio, Oscar, et al.
Published: (2022)
Memory Self-Regeneration: Uncovering Hidden Knowledge in Unlearned Models
by: Polowczyk, Agnieszka, et al.
Published: (2025)
by: Polowczyk, Agnieszka, et al.
Published: (2025)
Uncovering Bias Paths with LLM-guided Causal Discovery: An Active Learning and Dynamic Scoring Approach
by: Zanna, Khadija, et al.
Published: (2025)
by: Zanna, Khadija, et al.
Published: (2025)
Layer by Layer: Uncovering Hidden Representations in Language Models
by: Skean, Oscar, et al.
Published: (2025)
by: Skean, Oscar, et al.
Published: (2025)
Hidden in the Multiplicative Interaction: Uncovering Fragility in Multimodal Contrastive Learning
by: Rheude, Tillmann, et al.
Published: (2026)
by: Rheude, Tillmann, et al.
Published: (2026)
LINC: Decoupling Local Consequence Scoring from Hidden Matching in Constructive Neural Routing
by: Qin, Shaofeng, et al.
Published: (2026)
by: Qin, Shaofeng, et al.
Published: (2026)
Causal Entropy and Information Gain for Measuring Causal Control
by: Simoes, Francisco Nunes Ferreira Quialheiro, et al.
Published: (2023)
by: Simoes, Francisco Nunes Ferreira Quialheiro, et al.
Published: (2023)
Unraveling the Hidden Dynamical Structure in Recurrent Neural Policies
by: Li, Jin, et al.
Published: (2026)
by: Li, Jin, et al.
Published: (2026)
Beyond Over-smoothing: Uncovering the Trainability Challenges in Deep Graph Neural Networks
by: Peng, Jie, et al.
Published: (2024)
by: Peng, Jie, et al.
Published: (2024)
Deep Autoregressive Models as Causal Inference Engines
by: Im, Daniel Jiwoong, et al.
Published: (2024)
by: Im, Daniel Jiwoong, et al.
Published: (2024)
Ensemble Methods for Sequence Classification with Hidden Markov Models
by: Kawawa-Beaudan, Maxime, et al.
Published: (2024)
by: Kawawa-Beaudan, Maxime, et al.
Published: (2024)
Spectral Representation for Causal Estimation with Hidden Confounders
by: Sun, Haotian, et al.
Published: (2024)
by: Sun, Haotian, et al.
Published: (2024)
Uncovering Critical Sets of Deep Neural Networks via Sample-Independent Critical Lifting
by: Zhang, Leyang, et al.
Published: (2025)
by: Zhang, Leyang, et al.
Published: (2025)
Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges
by: Poinsot, Audrey, et al.
Published: (2024)
by: Poinsot, Audrey, et al.
Published: (2024)
Fundamental Properties of Causal Entropy and Information Gain
by: Simoes, Francisco N. F. Q., et al.
Published: (2024)
by: Simoes, Francisco N. F. Q., et al.
Published: (2024)
On Measuring Intrinsic Causal Attributions in Deep Neural Networks
by: Saha, Saptarshi, et al.
Published: (2025)
by: Saha, Saptarshi, et al.
Published: (2025)
Comparative Study of Causal Discovery Methods for Cyclic Models with Hidden Confounders
by: Lorbeer, Boris, et al.
Published: (2024)
by: Lorbeer, Boris, et al.
Published: (2024)
Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training
by: Xie, Jiancheng, et al.
Published: (2024)
by: Xie, Jiancheng, et al.
Published: (2024)
Provable Generalization Bounds for Deep Neural Networks with Momentum-Adaptive Gradient Dropout
by: Safder, Adeel
Published: (2025)
by: Safder, Adeel
Published: (2025)
Provable Accelerated Convergence of Nesterov's Momentum for Deep ReLU Neural Networks
by: Liao, Fangshuo, et al.
Published: (2023)
by: Liao, Fangshuo, et al.
Published: (2023)
Dynamic Bayesian Networks for Predicting Cryptocurrency Price Directions: Uncovering Causal Relationships
by: Amirzadeh, Rasoul, et al.
Published: (2023)
by: Amirzadeh, Rasoul, et al.
Published: (2023)
Conjugate Learning Theory: Uncovering the Mechanisms of Trainability and Generalization in Deep Neural Networks
by: Qi, Binchuan
Published: (2026)
by: Qi, Binchuan
Published: (2026)
Hidden Markov Neural Networks
by: Rimella, Lorenzo, et al.
Published: (2020)
by: Rimella, Lorenzo, et al.
Published: (2020)
Time-Varying Deep State Space Models for Sequences with Switching Dynamics
by: Karilanova, Sanja, et al.
Published: (2026)
by: Karilanova, Sanja, et al.
Published: (2026)
Discovering and Reasoning of Causality in the Hidden World with Large Language Models
by: Liu, Chenxi, et al.
Published: (2024)
by: Liu, Chenxi, et al.
Published: (2024)
Robust Causal Analysis of Linear Cyclic Systems With Hidden Confounders
by: Lorbeer, Boris, et al.
Published: (2024)
by: Lorbeer, Boris, et al.
Published: (2024)
Heterogeneous Graph Sequence Neural Networks for Dynamic Traffic Assignment
by: Liu, Tong, et al.
Published: (2024)
by: Liu, Tong, et al.
Published: (2024)
Fairness-Driven LLM-based Causal Discovery with Active Learning and Dynamic Scoring
by: Zanna, Khadija, et al.
Published: (2025)
by: Zanna, Khadija, et al.
Published: (2025)
Deep Sequence-to-Sequence Models for GNSS Spoofing Detection
by: Zelinka, Jan, et al.
Published: (2025)
by: Zelinka, Jan, et al.
Published: (2025)
Probabilistic Learning and Generation in Deep Sequence Models
by: Chen, Wenlong
Published: (2026)
by: Chen, Wenlong
Published: (2026)
Dynamic Momentum Recalibration in Online Gradient Learning
by: Yao, Zhipeng, et al.
Published: (2026)
by: Yao, Zhipeng, et al.
Published: (2026)
Neural Sequence-to-Sequence Modeling with Attention by Leveraging Deep Learning Architectures for Enhanced Contextual Understanding in Abstractive Text Summarization
by: Challagundla, Bhavith Chandra, et al.
Published: (2024)
by: Challagundla, Bhavith Chandra, et al.
Published: (2024)
Adaptive Memory Momentum via a Model-Based Framework for Deep Learning Optimization
by: Topollai, Kristi, et al.
Published: (2025)
by: Topollai, Kristi, et al.
Published: (2025)
Graph Neural Network Causal Explanation via Neural Causal Models
by: Behnam, Arman, et al.
Published: (2024)
by: Behnam, Arman, et al.
Published: (2024)
Similar Items
-
Learning to Play Air Hockey with Model-Based Deep Reinforcement Learning
by: Orsula, Andrej
Published: (2024) -
Uncovering Causal Relation Shifts in Event Sequences under Out-of-Domain Interventions
by: Zinat, Kazi Tasnim, et al.
Published: (2025) -
Score-based Generative Models with Adaptive Momentum
by: Wen, Ziqing, et al.
Published: (2024) -
Uncovering Hidden Systematics in Neural Network Models for High Energy Physics
by: Flek, Lucie, et al.
Published: (2026) -
Uncovering the Hidden Cost of Model Compression
by: Misra, Diganta, et al.
Published: (2023)