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Found 10 papers, 3 papers with code
From Pairwise to Ranking: Climbing the Ladder to Ideal Collaborative Filtering with Pseudo-Ranking
However, bridging the gap in practice encounters two formidable challenges: (1) none of the real-world datasets contains full ranking information; (2) there does not exist a loss function that is capable of consuming ranking information.
AI-driven emergence of frequency information non-uniform distribution via THz metasurface spectrum prediction
Recently, artificial intelligence has been extensively deployed across various scientific disciplines, optimizing and guiding the progression of experiments through the integration of abundant datasets, whilst continuously probing the vast theoretical space encapsulated within the data.
MLatom 3: Platform for machine learning-enhanced computational chemistry simulations and workflows
MLatom 3 is a program package designed to leverage the power of ML to enhance typical computational chemistry simulations and to create complex workflows.
The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation
In this paper, we summarize the winning solutions from the RoboDepth Challenge -- an academic competition designed to facilitate and advance robust OoD depth estimation.
A Cascade Dual-Decoder Model for Joint Entity and Relation Extraction
In this work, we propose an effective cascade dual-decoder method to extract overlapping relational triples, which includes a text-specific relation decoder and a relation-corresponded entity decoder.
Privacy-Preserving Federated Learning on Partitioned Attributes
Real-world data is usually segmented by attributes and distributed across different parties.
Optically reconfigurable quantum spin-valley Hall effect of light in coupled nonlinear ring resonator lattice
In optics, various photonic topological circuits have been developed, which were based on classical emulation of either quantum spin Hall effect or quantum valley Hall effect.
Optics
Learning to Prevent Leakage: Privacy-Preserving Inference in the Mobile Cloud
Powered by machine learning services in the cloud, numerous learning-driven mobile applications are gaining popularity in the market.
Deep Motion Blur Removal Using Noisy/Blurry Image Pairs
Thus, we propose to restore a sharp image by fusing a pair of noisy/blurry images captured in a burst.
GAN Based Image Deblurring Using Dark Channel Prior
A conditional general adversarial network (GAN) is proposed for image deblurring problem.
