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Found 11 papers, 2 papers with code
Graph Sparsification for Enhanced Conformal Prediction in Graph Neural Networks
Conformal Prediction is a robust framework that ensures reliable coverage across machine learning tasks.
Benchmarking Graph Conformal Prediction: Empirical Analysis, Scalability, and Theoretical Insights
Recent work in graph uncertainty quantification has built upon this approach for conformal graph prediction.
SYSML: StYlometry with Structure and Multitask Learning: Implications for Darknet Forum Migrant Analysis
Darknet market forums are frequently used to exchange illegal goods and services between parties who use encryption to conceal their identities.
Understanding Knowledge Gaps in Visual Question Answering: Implications for Gap Identification and Testing
After identifying KGs for each question, we examine the skew in the distribution of questions for each KG.
THOMAS: The Hegemonic OSU Morphological Analyzer using Seq2seq
This paper describes the OSU submission to the SIGMORPHON 2019 shared task, Crosslinguality and Context in Morphology.
LEAF-QA: Locate, Encode & Attend for Figure Question Answering
LEAF-QA being constructed from real-world sources, requires a novel architecture to enable question answering.
Network Representation Learning: Consolidation and Renewed Bearing
An important area of research that has emerged over the last decade is the use of graphs as a vehicle for non-linear dimensionality reduction in a manner akin to previous efforts based on manifold learning with uses for downstream database processing, machine learning and visualization.
Towards Open Intent Discovery for Conversational Text
Existing research for intent discovery model it as a classification task with a predefined set of known categories.
Forecasting Granular Audience Size for Online Advertising
Orchestration of campaigns for online display advertising requires marketers to forecast audience size at the granularity of specific attributes of web traffic, characterized by the categorical nature of all attributes (e. g. {US, Chrome, Mobile}).
Corpus-based Content Construction
Enterprise content writers are engaged in writing textual content for various purposes.
Generating Appealing Brand Names
Providing appealing brand names to newly launched products, newly formed companies or for renaming existing companies is highly important as it can play a crucial role in deciding its success or failure.
