Expanding the deployment envelope of behavior prediction via adaptive meta-learning
Learning-based behavior prediction methods are increasingly being deployed in real-world
autonomous systems, eg, in fleets of self-driving vehicles, which are beginning to …
autonomous systems, eg, in fleets of self-driving vehicles, which are beginning to …
Transferable and adaptable driving behavior prediction
While autonomous vehicles still struggle to solve challenging situations during on-road
driving, humans have long mastered the essence of driving with efficient, transferable, and …
driving, humans have long mastered the essence of driving with efficient, transferable, and …
TestFit: A plug-and-play one-pass test time method for medical image segmentation
Deep learning (DL) based methods have been extensively studied for medical image
segmentation, mostly emphasizing the design and training of DL networks. Only few …
segmentation, mostly emphasizing the design and training of DL networks. Only few …
Online Model Adaptation with Feedforward Compensation
A Abuduweili, C Liu - Conference on Robot Learning, 2023 - proceedings.mlr.press
To cope with distribution shifts or non-stationarity in system dynamics, online adaptation
algorithms have been introduced to update offline-learned prediction models in real-time …
algorithms have been introduced to update offline-learned prediction models in real-time …
Experimental evaluation of human motion prediction toward safe and efficient human robot collaboration
Human motion prediction is non-trivial in modern industrial settings. Accurate prediction of
human motion can not only improve efficiency in human-robot collaboration, but also …
human motion can not only improve efficiency in human-robot collaboration, but also …
Robust nonlinear adaptation algorithms for multitask prediction networks
A Abuduweili, C Liu - … Journal of Adaptive Control and Signal …, 2021 - Wiley Online Library
High fidelity behavior prediction of intelligent agents is critical in many applications, which is
challenging due to the stochasticity, heterogeneity, and time‐varying nature of agent …
challenging due to the stochasticity, heterogeneity, and time‐varying nature of agent …
A General Calibrated Regret Metric for Detecting and Mitigating Human-Robot Interaction Failures
Robot decision-making increasingly relies on expressive data-driven human prediction
models when operating around people. While these models are known to suffer from …
models when operating around people. While these models are known to suffer from …
Stationary Latent Weight Inference for Unreliable Observations from Online Test-Time Adaptation
In the rapidly evolving field of online test-time adaptation (OTTA), effectively managing
distribution shifts is a pivotal concern. State-of-the-art OTTA methodologies often face …
distribution shifts is a pivotal concern. State-of-the-art OTTA methodologies often face …