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08/20/2023
Scaled-up Discovery of Latent Concepts in Deep NLP Models
Pre-trained language models (pLMs) learn intricate patterns and contextu...
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10/12/2022
DiPA: Diverse and Probabilistically Accurate Interactive Prediction
Accurate prediction is important for operating an autonomous vehicle in ...
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07/29/2022
Perspectives on the System-level Design of a Safe Autonomous Driving Stack
Achieving safe and robust autonomy is the key bottleneck on the path tow...
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06/22/2022
Beyond RMSE: Do machine-learned models of road user interaction produce human-like behavior?
Autonomous vehicles use a variety of sensors and machine-learned models ...
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11/01/2020
PILOT: Efficient Planning by Imitation Learning and Optimisation for Safe Autonomous Driving
Achieving the right balance between planning quality, safety and runtime...
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02/06/2020
A Two-Stage Optimization Approach to Safe-by-Design Planning for Autonomous Driving
Lessons learned from the increasing diversity of road trial deployments ...
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01/07/2020
PaRoT: A Practical Framework for Robust Deep NeuralNetwork Training
Deep Neural Networks (DNNs) are finding important applications in safety...
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01/07/2020
PaRoT: A Practical Framework for Robust Deep Neural Network Training
Deep Neural Networks (DNNs) are finding important applications in safety...
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04/15/2018
Efficient Computation of Collision Probabilities for Safe Motion Planning
We address the problem of safe motion planning. As mobile robots and aut...
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09/11/2017
CLAD: A Complex and Long Activities Dataset with Rich Crowdsourced Annotations
This paper introduces a novel activity dataset which exhibits real-life ...
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07/25/2016
Estimating Activity at Multiple Scales using Spatial Abstractions
Autonomous robots operating in dynamic environments must maintain belief...
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05/01/2015