Publications (16)
HybridFlow: A Two-Step Generative Policy for Robotic Manipulation
Zhenchen Dong, Jinna Fu, Jiaming Wu +3
Limited by inference latency, existing robot manipulation policies lack sufficient real-time interaction capability with the environment. Although faster generation methods such as…
The large-scale charging scheduling problem for fleet batteries: Lagrangian decomposition with time-block reformulations
Sunney Fotedar, Jiaming Wu, Balazs Kulcsar +1
There is a rise in the need for efficient battery charging methods due to the high penetration of electromobility solutions. Battery swapping, a technique in which fully or partial…
Beyond Simple Graphs: Neural Multi-Objective Routing on Multigraphs
Filip Rydin, Attila Lischka, Jiaming Wu +2
Learning-based methods for routing have gained significant attention in recent years, both in single-objective and multi-objective contexts. Yet, existing methods are unsuitable fo…
YOLO-LLTS: Real-Time Low-Light Traffic Sign Detection via Prior-Guided Enhancement and Multibranch Feature Interaction
Ziyu Lin, Yunfan Wu, Yuhang Ma +5
Traffic sign detection is essential for autonomous driving and Advanced Driver Assistance Systems (ADAS). However, existing methods struggle to address the challenges of poor image…
The Cooperative Sorting Strategy for Connected and Automated Vehicle Platoons
Jiaming Wu, Soyoung Ah, Yang Zhou +2
This paper presents a "cooperative vehicle sorting" strategy that seeks to optimally sort connected and automated vehicles (CAVs) in a multi-lane platoon to reach an ideally organi…
Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation
Yee Hin Chong, Jiaming Wu, Youhui Zhang +1
Large language models (LLMs) have shown strong empirical gains as self-evolving agents for CUDA kernel generation, driven by feedback-conditioned planning across generations. Howev…
Collaborative Charging Scheduling via Balanced Bounding Box Methods
Fangting Zhou, Balazs Kulcsar, Jiaming Wu
Electric mobility faces several challenges, most notably the high cost of infrastructure development and the underutilization of charging stations. The concept of shared charging o…
A dynamical memory with only one spiking neuron
Damien Depannemaecker, Adrien d'Hollande, Jiaming Wu +1
Common wisdom indicates that to implement a Dynamical Memory with spiking neurons two ingredients are necessary: recurrence and a neuron population. Here we shall show that the sec…
Quantifying white matter hyperintensity and brain volumes in heterogeneous clinical and low-field portable MRI
Pablo Laso, Stefano Cerri, Annabel Sorby-Adams +21
Brain atrophy and white matter hyperintensity (WMH) are critical neuroimaging features for ascertaining brain injury in cerebrovascular disease and multiple sclerosis. Automated se…
Collaborative electric vehicle routing with meet points
Fangting Zhou, Ala Arvidsson, Jiaming Wu +1
In this paper, we develop a profit-sharing-based optimal routing mechanism to incentivize horizontal collaboration among urban goods distributors. This paper investigates a collabo…
Less Is More -- On the Importance of Sparsification for Transformers and Graph Neural Networks for TSP
Attila Lischka, Jiaming Wu, Rafael Basso +2
Most of the recent studies tackling routing problems like the Traveling Salesman Problem (TSP) with machine learning use a transformer or Graph Neural Network (GNN) based encoder a…
Deep Image-based Illumination Harmonization
Zhongyun Bao, Chengjiang Long, Gang Fu +4
Integrating a foreground object into a background scene with illumination harmonization is an important but challenging task in computer vision and augmented reality community. Exi…
Joint Planning and Scheduling of Modular Vehicles for Passenger-Freight Integration
Wanru Chen, Jiaming Wu, Balázs Kulcsár
This paper proposes a modular vehicle system for passenger-freight integration along a bidirectional transit corridor. The system uses homogeneous units that can be coupled into ve…
Learning for routing: A guided review of recent developments and future directions
Fangting Zhou, Attila Lischka, Balazs Kulcsar +3
This paper reviews the current progress in applying machine learning (ML) tools to solve NP-hard combinatorial optimization problems, with a focus on routing problems such as the t…
A GREAT Architecture for Edge-Based Graph Problems Like TSP
Attila Lischka, Filip Rydin, Jiaming Wu +2
In the last years, an increasing number of learning-based approaches have been proposed to tackle combinatorial optimization problems such as routing problems. Many of these approa…
A user-driven pricing and scheduling framework for public electric vehicle charging
Fangting Zhou, Jiaming Wu, Balazs Kulcsar
Public electric vehicle (EV) charging infrastructure has expanded rapidly, yet utilization across charging stations remains uneven and often inefficient. Existing operator-determin…