Titlebook: Artificial Intelligence Research; Third Southern Afric Anban Pillay,Edgar Jembere,Aurona Gerber Conference proceedings 2022 The Editor(s) (

Pander

Ingratiate

Jacobian Norm Regularisation and Conditioning in Neural ODEsuations needed by a numerical ODE solver during training. For instance, in the context of continuous normalising flows, the Frobenius norm of Jacobian matrices are regularised under the hypothesis that complex dynamics relate to an ill-conditioned ODE and require more function evaluations from the s

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Improving Cause-of-Death Classification from Verbal Autopsy Reportsality policies. Further, since clinical data is unique to individual institutions and laboratories, there are insufficient data annotation standards and conventions. As a result of the scarcity of textual data, natural language processing (NLP) techniques have fared poorly in the health sector. A ca

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Airtight

Ischemia

ST-GNNs for Weather Prediction in South Africafor weather prediction applications. We compare and evaluate Graph WaveNet (GWN) and the Low Rank Weighted Graph Neural Network (WGN) for weather prediction in South Africa. We compare these results to two basic temporal deep neural networks architectures, i.e. the Long Short-Term Memory (LSTM) and

教唆

endarterectomy

Cauchy Loss Function: Robustness Under Gaussian and Cauchy Noisetly used mean squared error (MSE) loss assumes a Gaussian noise distribution. The choice of loss function during training and testing affects the performance of artificial neural networks (ANNs). It is known that MSE may yield substandard performance in the presence of outliers. The Cauchy loss func

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CASA: Cricket Action Similarity Assessment in Video Footage Using Deep Metric Learning Assessment is the task of comparing the similarity or dissimilarity of an action between two actors to determine how similar the actions they perform are to one another. This research paper proposes the use of a Siamese Convolution Neural Network to compute the similarity distances between differen

重力

From GNNs to Sparse Transformers: Graph-Based Architectures for Multi-hop Question Answeringhat the Transformer is a particular message passing GNN, in this paper we perform an architectural analysis and evaluation to investigate why the Transformer outperforms other GNNs on MHQA. We simplify existing GNN-based MHQA models and leverage this system to compare GNN architectures in a lower co