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07/19/2023
Explaining Autonomous Driving Actions with Visual Question Answering
The end-to-end learning ability of self-driving vehicles has achieved si...
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03/05/2023
Reparameterization through Spatial Gradient Scaling
Reparameterization aims to improve the generalization of deep neural net...
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02/21/2023
A General-Purpose Transferable Predictor for Neural Architecture Search
Understanding and modelling the performance of neural architectures is k...
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11/30/2022
AIO-P: Expanding Neural Performance Predictors Beyond Image Classification
Evaluating neural network performance is critical to deep neural network...
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11/30/2022
GENNAPE: Towards Generalized Neural Architecture Performance Estimators
Predicting neural architecture performance is a challenging task and is ...
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12/21/2021
Explainable Artificial Intelligence for Autonomous Driving: A Comprehensive Overview and Field Guide for Future Research Directions
Autonomous driving has achieved a significant milestone in research and ...
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11/20/2021
Towards safe, explainable, and regulated autonomous driving
There has been growing interest in the development and deployment of aut...
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09/25/2021
L^2NAS: Learning to Optimize Neural Architectures via Continuous-Action Reinforcement Learning
Neural architecture search (NAS) has achieved remarkable results in deep...
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05/19/2021
Generative Adversarial Neural Architecture Search
Despite the empirical success of neural architecture search (NAS) in dee...
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09/01/2020