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Found 11 papers, 6 papers with code
DynGL-SDP: Dynamic Graph Learning for Semantic Dependency Parsing
A recent success in semantic dependency parsing shows that graph neural networks can make significant accuracy improvements, owing to its powerful ability in learning expressive graph representations.
Disturbance Rejection-Guarded Learning for Vibration Suppression of Two-Inertia Systems
On the other hand, machine learning benefits from an additional assurance layer provided by the ESO, as any imperfections in the machine learning model can be compensated for by the ESO.
ContraNovo: A Contrastive Learning Approach to Enhance De Novo Peptide Sequencing
De novo peptide sequencing from mass spectrometry (MS) data is a critical task in proteomics research.
Robust Control Barrier Functions for Safe Control Under Uncertainty Using Extended State Observer and Output Measurement
Our approach provides a less conservative estimation error bound than other disturbance observer-based CBFs.
Towards Better Robustness against Common Corruptions for Unsupervised Domain Adaptation
Recent studies have investigated how to achieve robustness for unsupervised domain adaptation (UDA).
A General Model-Based Extended State Observer with Built-In Zero Dynamics
A general model-based extended state observer (GMB-ESO) is proposed for single-input single-output linear time-invariant systems with a given state space model, where the total disturbance, a lump sum of model uncertainties and external disturbances, is defined as an extended state in the same manner as in the original formulation of ESO.
A Higher-Order Semantic Dependency Parser
Higher-order features bring significant accuracy gains in semantic dependency parsing.
CDNet: Centripetal Direction Network for Nuclear Instance Segmentation
Specifically, we define the centripetal direction feature as a class of adjacent directions pointing to the nuclear center to represent the spatial relationship between pixels within the nucleus.
Gradient Distribution Alignment Certificates Better Adversarial Domain Adaptation
In particular, we show that the distribution discrepancy can be reduced by constraining feature gradients of two domains to have similar distributions.
An AI-based, Multi-stage detection system of banking botnets
Banking Trojans, botnets are primary drivers of financially-motivated cybercrime.
Evaluating Ensemble Based Pre-annotation on Named Entity Corpus Construction in English and Chinese
Annotated corpora are crucial language resources, and pre-annotation is an usual way to reduce the cost of corpus construction.
