4 accepted papers
We present a novel framework for embedding hard constraint satisfaction into neural network (NN) architectures, specifically feedforward neural networks and transformers, with input-dependent affine constraints of arbitrary cardinality. Traditional constraint enforcement approaches either rely on pe…
Diffusion-based planners have achieved generalization comparable to classical planners by leveraging inference-time optimization through guidance. However, their limited ability to capture environmental variations often constrains their responsiveness in unseen settings. In addition, the diversity-c…
Existing Autonomous Mobility-on-Demand (AMoD) systems and demand-responsive algorithms are designed to adaptively respond to traffic demands, enhancing traffic service quality and profitability. However, such approaches may exacerbate traffic congestion by concentrating vehicles in high-demand areas
We introduce a method to generate temporally coherent human animation from a single image, a video, or a random noise. This problem has been formulated as modeling of an auto-regressive generation, i.e., to regress past frames to decode future frames. However, such unidirectional generation is highl…