Genre
Articulate your NeRF: Unsupervised articulated object modeling via conditional view synthesis
Articulated objects, composed of multiple rigid parts connected by joints allowing rotational or translational motion, such as doors, cupboards and spectacles are ubiquitous in our daily lives.
Learning diverse causally emergent representations from time series data
Cognitive processes usually take place at a macroscopic scale in systems charac-terised by emergent properties that make the whole'more than the sum of its parts.'
Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight Adjustment
To avoid redundancy in these synthetic datasets, it is crucial that each element contains unique features and remains diverse from others during the synthesis stage. In this paper, we provide a thorough theoretical and empirical analysis of diversity within synthesized datasets. We argue that enhancing diversity can improve the parallelizable yet isolated synthesizing approach.
