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PhD Thesis Defense
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PhD Thesis Defense
Learning and Inference in Factor Graphs with Applications to Tactile Perception
Abstract: Factor graphs offer a flexible and powerful framework for solving large-scale, nonlinear inference problems as encountered in robot perception and control. Typically, these methods rely on handcrafted models that are efficient to optimize. However, robots often perceive the world through complex, high-dimensional sensor observations. For instance, consider a robot manipulating an object in hand [...]
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Robotics Institute,
Carnegie Mellon University
Carnegie Mellon University