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Environment prediction frameworks are integral for autonomous vehicles, enabling safe navigation in dynamic environments.
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DeepMDP: Learning continuous latent space models for representation learning
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PyTorch Lightning, Mar. 2019
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Learning latent representations to influence multi-agent interaction
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Deep latent competition: Learning to race using visual control policies in latent space
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MELD: Meta-reinforcement learning from images via latent state models
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PLAS: Latent action space for offline reinforcement learning
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Denoising diffusion implicit models
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Occupancy flow fields for motion forecasting in autonomous driving
R. Mahjourian, J. Kim, Y. Chai, M. Tan, B. Sapp, and D. Anguelov · 2022
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Scept: Scene-consistent, policy-based trajectory predictions for planning
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How do we fail? stress testing perception in autonomous vehicles
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Motion transformer with global intention localization and local movement refinement
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Dynamics-aware spatiotemporal occupancy prediction in urban environments
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Self-supervised point cloud prediction using 3d spatio-temporal convolutional networks
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Video diffusion models
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Simvp: Simpler yet better video prediction
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Interpretable self-aware neural networks for robust trajectory prediction
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Multi-agent variational occlusion inference using people as sensors
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Survey on lidar perception in adverse weather conditions
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