AD-MLP: Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes [Baidu] The Shift from Models to Compound AI Systems Roach: End-to-End Urban Driving by Imitating a Reinforcement Learning Coach ICCV 2021 Learning from All Vehicles CVPR 2022 LBC: Learning by Cheating CoR...
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To decouple a specific implementation of this data model from a logical schema that can be adapted without imposing a new software dependency, we describe a set of data structures that address two distinct needs in multi-animal pose tracking: training data and predictions. We provide a detailed ...
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The learning task is then to fill in the holes. Examples of NeSy systems based on sketching are DeepProbLog and ∂4, which fill in the holes in a (symbolic) program via neural networks. The advantage of sketching is that it provides a nice interface for NeSy systems, as the holes ...
Deep learning-based anomaly detection in cyber-physical systems: Progress and oportunities. ACM Computing Surveys, 2022. paper Yuan Luo, Ya Xiao, Long Cheng, Guojun Peng, and Danfeng (Daphne) Yao. GAN-based anomaly detection: A review. Neurocomputing, 2022. paper Xuan Xia, Xizhou Pan, Nan...
The Hamiltonian reshaping technique used in this work is similar in spirit to the commonly used dynamical decoupling technique61,62. In fact, for quantum systems with simple geometry, such as a 1D chain, dynamical decoupling can be readily used to decouple it into isolated clusters, which is on...
As results show, learnable keys play an important role to decouple the query and prompt learning processes. Table 5 (row 3) removes the diversified prompt selection (only used in 5-dataset ex- periments). Basically, removing it allows instances from different tasks to choose prompts freely. ...
Furthermore, the NN based ML technique is a tool, which has been successfully applied to coupled systems [22,23]. However, the ML are applied for either the prediction of individual parameters or upscaling of process. The issue of ML for the multi-physics calculation of a complex underground...
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习 - transferlearning/doc/transfer_learning_application.md at master · jindongwang/transferlearning