main webpage W Topic Load (Album) arXiv (Cornell University) Gait-Based Hand Load Estimation via Deep Latent Variable Models with Auxiliary Information 2025 Machine learning methods are increasingly applied to ergonomic risk assessment in manual material handling, particularly for estimating carried load from gait motion data collected from wearable sensors. However, existing approaches often rely on direct mappi… Article Open Load (Album) Open Article Page

Load (Album)

1996 studio album by Metallica Load is the sixth studio album by American heavy metal band Metallica, released on June 4, 1996, by Elektra Records in the United States and by Vertigo Records internationally. The album showed more of a hard rock side of Metallica than the band's typical thrash metal style, which alienated much of the band's fanbase. It also featured influences from genres such as Southern rock, blues rock, country rock, and alternative rock. Drummer Lars Ulrich said about Load 's more exploratory nature, "This album and what we're doing with it – that, to me, is what Metallica are all about: exploring different things. The minute you stop exploring, then just sit down and fucking die." At 79 minutes, Load is Metallica's longest studio album. Critical Symbolic Virtual Narrative Open Load (Album) Open Article Page

Exploring foci of: arXiv (Cornell University) Gait-Based Hand Load Estimation via Deep Latent Variable Models with Auxiliary Information 2025 Machine learning methods are increasingly applied to ergonomic risk assessment in manual material handling, particularly for estimating carried load from gait motion data collected from wearable sensors. However, existing approaches often rely on direct mappings from loaded gait to hand load, limiting generalization and predictive accuracy. In this study, we propose an enhanced load estimation framework that incorporates auxiliary information, including baseline gait patterns during unloaded walking and carrying s… Open Article Page

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Explore Load (Album) W Topic Load (Album) arXiv (Cornell University) Gait-Based Hand Load Estimation via Deep Latent Variable Models with Auxiliary Information 2025 Machine learning methods are increasingly applied to ergonomic risk assessment in manual material handling, particularly for estimating carried load from gait motion data collected from wearable sensors. However, existing approaches often rely on direct mappi… Article Critical Symbolic Virtual Narrative Open Load (Album) Open Article Page