Graph Neural Networks (GNNs) are state-of-the-art models for performing
...
Adapters, a plug-in neural network module with some tunable parameters, ...
We present MatSci-NLP, a natural language benchmark for evaluating the
p...
Multi-organ segmentation, which identifies and separates different organ...
Recommendation models that utilize unique identities (IDs) to represent
...
Crash sequence analysis has been shown in prior studies to be useful for...
Strong lensing in galaxy clusters probes properties of dense cores of da...
This paper develops a test scenario specification procedure using crash
...
Online meal delivery is undergoing explosive growth, as this service is
...
User interest exploration is an important and challenging topic in
recom...
With safety being one of the primary motivations for developing automate...
The standard petrography test method for measuring air voids in concrete...
Despite enormous efforts over the last decades to establish the relation...
To achieve robust and accurate state estimation for robot navigation, we...
High fidelity reproductions of paintings provide new opportunities to mu...
In the preliminary trajectory design of the multi-target rendezvous prob...
In the preliminary trajectory design of the multi-target rendezvous prob...
In the preliminary trajectory design of the multi-target rendezvous prob...
This paper presents a novel methodology for solving the time-optimal
tra...
Transit signal priority (TSP) has been implemented to transit systems in...
As an emerging field, Automated Machine Learning (AutoML) aims to reduce...
Existing simultaneous localization and mapping (SLAM) algorithms are not...
The problem of fitting a union of subspaces to a collection of data poin...
Subspace clustering refers to the problem of segmenting a set of data po...