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Found 10 papers, 1 papers with code
WeakSurg: Weakly supervised surgical instrument segmentation using temporal equivariance and semantic continuity
Weakly supervised surgical instrument segmentation with only instrument presence labels has been rarely explored in surgical domain.
FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design
Addressing this, we introduce \textsc{FinMem}, a novel LLM-based agent framework devised for financial decision-making.
Stand for Something or Fall for Everything: Predict Misinformation Spread with Stance-Aware Graph Neural Networks
Although pervasive spread of misinformation on social media platforms has become a pressing challenge, existing platform interventions have shown limited success in curbing its dissemination.
Instant Photorealistic Style Transfer: A Lightweight and Adaptive Approach
In this paper, we propose an Instant Photorealistic Style Transfer (IPST) approach, designed to achieve instant photorealistic style transfer on super-resolution inputs without the need for pre-training on pair-wise datasets or imposing extra constraints.
MURPHY: Relations Matter in Surgical Workflow Analysis
Autonomous robotic surgery has advanced significantly based on analysis of visual and temporal cues in surgical workflow, but relational cues from domain knowledge remain under investigation.
Improving Global Forest Mapping by Semi-automatic Sample Labeling with Deep Learning on Google Earth Images
To provide guidelines for users and producers, it is urgent to produce a validation sample set at the global level.
Stochastic Top-k ListNet
ListNet is a well-known listwise learning to rank model and has gained much attention in recent years.
Learning from LDA using Deep Neural Networks
Latent Dirichlet Allocation (LDA) is a three-level hierarchical Bayesian model for topic inference.
Bayesian Analysis for miRNA and mRNA Interactions Using Expression Data
Compared to the point estimate algorithms, which only provide single estimates for those parameters, the Bayesian methods are more meaningful and provide credible intervals, which take into account the uncertainty of the inferred interactions of the miRNA and mRNA.
