Delve into the cutting edge of Artificial Intelligence with our dedicated Research Paper section.
![Inverse analysis of granular flows using differentiable graph neural network simulator. (arXiv:2401.13695v1 [physics.geo-ph])](http://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png "Inverse analysis of granular flows using differentiable graph neural network simulator. (arXiv:2401.13695v1 [physics.geo-ph])"){kind=logo}
Inverse problems in granular flows, such as landslides and debris flows, involve estimating material parameters or boundary conditions based on target runout profile. Traditional high-fidelity simulators for these inverse problems are computationally demanding, restricting the number of simulations possible. Additionally,…
Unsupervised Domain Adaptation for Regression (UDAR) aims to adapt a model from a labeled source domain to an unlabeled target domain for regression tasks. Recent successful works in UDAR mostly focus on subspace alignment, involving the alignment of a selected…
In current text-based task-oriented dialogue (TOD) systems, user emotion detection (ED) is often overlooked or is typically treated as a separate and independent task, requiring additional training. In contrast, our work demonstrates that seamlessly unifying ED and TOD modeling brings…
Convolutional neural networks have shown to be widely applicable to a large number of fields when large amounts of labelled data are available. The recent trend has been to use models with increasingly larger sets of tunable parameters to increase…
Discovering Salient Neurons in deep NLP models Nadir Durrani, Fahim Dalvi, Hassan Sajjad; 24(362):1−40, 2023. Abstract While a lot of work has been done in understanding representations learned within deep NLP models and what knowledge they capture, work done towards…
Challenges can be seen as a type of game that motivates participants to solve serious tasks. As a result, competition organizers must develop effective game rules. However, these rules have multiple objectives beyond making the game enjoyable for participants. These…
The application of process mining for unstructured data might significantly elevate novel insights into disciplines where unstructured data is a common data format. To efficiently analyze unstructured data by process mining and to convey confidence into the analysis result, requires…
Face recognition (FR) has been applied to nearly every aspect of daily life, but it is always accompanied by the underlying risk of leaking private information. At present, almost all attack models against FR rely heavily on the presence of…
[Submitted on 24 Jan 2024] Download a PDF of the paper titled Tweets to Citations: Unveiling the Impact of Social Media Influencers on AI Research Visibility, by Iain Xie Weissburg and 3 other authors Download PDF Abstract:As the number of…
In response to everyday queries, humans explicitly signal uncertainty and offer alternative answers when they are unsure. Machine learning models that output calibrated prediction sets through conformal prediction mimic this human behaviour; larger sets signal greater uncertainty while providing alternatives.…
Off-Policy Actor-Critic with Emphatic Weightings Eric Graves, Ehsan Imani, Raksha Kumaraswamy, Martha White; 24(146):1−63, 2023. Abstract A variety of theoretically-sound policy gradient algorithms exist for the on-policy setting due to the policy gradient theorem, which provides a simplified form for…
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