What is the effect of running-specific prostheses on long jumps? Optimization-based prediction and analysis using biomechanical models
研究使用生物力学模型和优化控制方法,分析了跑步专用假肢对膝下截肢运动员跳远表现的影响,并比较了有无假肢的跳远运动。
研究使用生物力学模型和优化控制方法,分析了跑步专用假肢对膝下截肢运动员跳远表现的影响,并比较了有无假肢的跳远运动。
This work addresses the challenge of modeling heterogeneous features in soccer event data, where traditional one-hot or ordinal encodings fail to capture semantic relationships among categorical variables. The study proposes the first application of TabTransformer to soccer event representation learning, leveraging learnable dense embeddings and self-attention mechanisms to capture sport-specific action semantics during pretraining and generate general-purpose event representations. By effectively modeling latent dependencies among categorical features, the approach significantly outperforms baseline models on downstream tasks such as action value estimation and playing style recognition. Moreover, improved Brier scores demonstrate that the model yields better-calibrated predictive probabilities.
研究使用生物力学模型和优化控制方法,分析了跑步专用假肢对膝下截肢运动员跳远表现的影响,并比较了有无假肢的跳远运动。
This work addresses the challenge of modeling heterogeneous features in soccer event data, where traditional one-hot or ordinal encodings fail to capture semantic relationships among categorical variables. The study proposes the first application of TabTransformer to soccer event representation learning, leveraging learnable dense embeddings and self-attention mechanisms to capture sport-specific action semantics during pretraining and generate general-purpose event representations. By effectively modeling latent dependencies among categorical features, the approach significantly outperforms baseline models on downstream tasks such as action value estimation and playing style recognition. Moreover, improved Brier scores demonstrate that the model yields better-calibrated predictive probabilities.