Top Transportation & Logistics papers

Find all the Top AITransportation & Logistics papers. Links to pdf, code repos and demos are provided.

•

over 1 year ago

Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions

Michael. I. Jordan, Anastasios Nikolas Angelopoulos, Jordan Lekeufack + 2 more

We introduce Conformal Decision Theory, a framework for producing safe autonomous decisions despite imperfect machine learning predictions. Examples o...
see more

Computer Vision

almost 2 years ago

Doubly Robust Self-Training

Ming-Hui Wu, Michael. I. Jordan, Philip L Jacobson + 4 more

Self-training is an important technique for solving semi-supervised learning problems. It leverages unlabeled data by generating pseudo-labels and com...
see more

almost 4 years ago

On the Theory of Reinforcement Learning with Once-per-Episode Feedback

NeurIPS • Michael. I. Jordan, Niladri S. Chatterji, Aldo Pacchiano + 1 more

We study a theory of reinforcement learning (RL) in which the learner receives binary feedback only once at the end of an episode. While this is an ex...
see more

Tabular

about 15 years ago

Bayesian Nonparametric Inference of Switching Linear Dynamical Systems

Emily B. Fox, Michael. I. Jordan, Erik B. Sudderth + 1 more

Introduces a Bayesian nonparametric framework for inferring switching linear dynamical systems (SLDS) and switching vector autoregressive (VAR) proces...
see more

about 3 years ago

Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets

Michael. I. Jordan, Yifei Min, Tianhao Wang + 3 more

We study a Markov matching market involving a planner and a set of strategic agents on the two sides of the market. At each step, the agents are prese...
see more

Audio

about 5 years ago

DashCam Pay: A System for In-vehicle Payments Using Face and Voice

Cori Tymoszek, Sunpreet S. Arora, Kim Wagner + 1 more

We present our ongoing work on developing a system, called DashCam Pay, that enables in-vehicle payments in a seamless and secure manner using face an...
see more

Multimodal

11 months ago

Radar Fields: Frequency-Space Neural Scene Representations for FMCW Radar

David Borts, Erich Liang, Tim Brödermann + 9 more

Neural fields have been broadly investigated as scene representations for the reproduction and novel generation of diverse outdoor scenes, including t...
see more

Language

Computer Vision

about 1 year ago

Language-Guided Instance-Aware Domain-Adaptive Panoptic Segmentation

Elham Amin Mansour, Ozan Unal, Suman Saha + 2 more

The increasing relevance of panoptic segmentation is tied to the advancements in autonomous driving and AR/VR applications. However, the deployment of...
see more

about 1 year ago

GlORIE-SLAM: Globally Optimized RGB-only Implicit Encoding Point Cloud SLAM

Martin Ralf Oswald, Erik Sandstrom, Ganlin Zhang + 3 more

Recent advancements in RGB-only dense Simultaneous Localization and Mapping (SLAM) have predominantly utilized grid-based neural implicit encodings an...
see more

Computer Vision

about 1 year ago

Vanishing-Point-Guided Video Semantic Segmentation of Driving Scenes

CVPR • Diandian Guo, Deng-Ping Fan, Tongyu Lu + 2 more

The estimation of implicit cross-frame correspondences and the high computational cost have long been major challenges in video semantic segmentation ...
see more

Computer Vision

over 1 year ago

Diffusion-Based Particle-DETR for BEV Perception

Asen Nachkov, Martin Danelljan, Danda Pani Paudel + 1 more

The Bird-Eye-View (BEV) is one of the most widely-used scene representations for visual perception in Autonomous Vehicles (AVs) due to its well suited...
see more

Computer Vision

Multimodal

over 1 year ago

G-MEMP: Gaze-Enhanced Multimodal Ego-Motion Prediction in Driving

M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel + 5 more

Understanding the decision-making process of drivers is one of the keys to ensuring road safety. While the driver intent and the resulting ego-motion ...
see more

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Top Transportation & Logistics papers

Find all the Top AITransportation & Logistics papers. Links to pdf, code repos and demos are provided.

•

over 1 year ago

Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions

Michael. I. Jordan, Anastasios Nikolas Angelopoulos, Jordan Lekeufack + 2 more

We introduce Conformal Decision Theory, a framework for producing safe autonomous decisions despite imperfect machine learning predictions. Examples o...
see more

Computer Vision

almost 2 years ago

Doubly Robust Self-Training

Ming-Hui Wu, Michael. I. Jordan, Philip L Jacobson + 4 more

Self-training is an important technique for solving semi-supervised learning problems. It leverages unlabeled data by generating pseudo-labels and com...
see more

almost 4 years ago

On the Theory of Reinforcement Learning with Once-per-Episode Feedback

NeurIPS • Michael. I. Jordan, Niladri S. Chatterji, Aldo Pacchiano + 1 more

We study a theory of reinforcement learning (RL) in which the learner receives binary feedback only once at the end of an episode. While this is an ex...
see more

Tabular

about 15 years ago

Bayesian Nonparametric Inference of Switching Linear Dynamical Systems

Emily B. Fox, Michael. I. Jordan, Erik B. Sudderth + 1 more

Introduces a Bayesian nonparametric framework for inferring switching linear dynamical systems (SLDS) and switching vector autoregressive (VAR) proces...
see more

about 3 years ago

Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets

Michael. I. Jordan, Yifei Min, Tianhao Wang + 3 more

We study a Markov matching market involving a planner and a set of strategic agents on the two sides of the market. At each step, the agents are prese...
see more

Audio

about 5 years ago

DashCam Pay: A System for In-vehicle Payments Using Face and Voice

Cori Tymoszek, Sunpreet S. Arora, Kim Wagner + 1 more

We present our ongoing work on developing a system, called DashCam Pay, that enables in-vehicle payments in a seamless and secure manner using face an...
see more

Multimodal

11 months ago

Radar Fields: Frequency-Space Neural Scene Representations for FMCW Radar

David Borts, Erich Liang, Tim Brödermann + 9 more

Neural fields have been broadly investigated as scene representations for the reproduction and novel generation of diverse outdoor scenes, including t...
see more

Language

Computer Vision

about 1 year ago

Language-Guided Instance-Aware Domain-Adaptive Panoptic Segmentation

Elham Amin Mansour, Ozan Unal, Suman Saha + 2 more

The increasing relevance of panoptic segmentation is tied to the advancements in autonomous driving and AR/VR applications. However, the deployment of...
see more

about 1 year ago

GlORIE-SLAM: Globally Optimized RGB-only Implicit Encoding Point Cloud SLAM

Martin Ralf Oswald, Erik Sandstrom, Ganlin Zhang + 3 more

Recent advancements in RGB-only dense Simultaneous Localization and Mapping (SLAM) have predominantly utilized grid-based neural implicit encodings an...
see more

Computer Vision

about 1 year ago

Vanishing-Point-Guided Video Semantic Segmentation of Driving Scenes

CVPR • Diandian Guo, Deng-Ping Fan, Tongyu Lu + 2 more

The estimation of implicit cross-frame correspondences and the high computational cost have long been major challenges in video semantic segmentation ...
see more

Computer Vision

over 1 year ago

Diffusion-Based Particle-DETR for BEV Perception

Asen Nachkov, Martin Danelljan, Danda Pani Paudel + 1 more

The Bird-Eye-View (BEV) is one of the most widely-used scene representations for visual perception in Autonomous Vehicles (AVs) due to its well suited...
see more

Computer Vision

Multimodal

over 1 year ago

G-MEMP: Gaze-Enhanced Multimodal Ego-Motion Prediction in Driving

M. Eren Akbiyik, Nedko Savov, Danda Pani Paudel + 5 more

Understanding the decision-making process of drivers is one of the keys to ensuring road safety. While the driver intent and the resulting ego-motion ...
see more