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Found 5 papers, 2 papers with code
TimeGNN: Temporal Dynamic Graph Learning for Time Series Forecasting
Time series forecasting lies at the core of important real-world applications in many fields of science and engineering.
Time Series Forecasting Models Copy the Past: How to Mitigate
Recently neural network architectures have been widely applied to the problem of time series forecasting.
Image Keypoint Matching using Graph Neural Networks
Image matching is a key component of many tasks in computer vision and its main objective is to find correspondences between features extracted from different natural images.
Grounding Open-Domain Instructions to Automate Web Support Tasks
RUSS consists of two models: First, a BERT-LSTM with pointers parses instructions to ThingTalk, a domain-specific language we design for grounding natural language on the web.
Ehrhart-Equivalence, Equidecomposability, and Unimodular Equivalence of Integral Polytopes
In this paper, we establish a relationship between Ehrhart-equivalence and other forms of equivalence: the $\operatorname{GL}_n(\mathbb{Z})$-equidecomposability and unimodular equivalence of two integral $n$-polytopes in $\mathbb{R}^n$.
Combinatorics
