Presenter: Amangel Bhullar
Date: Friday, March 28th, 2025
Time: 1:00 pm
Location: Workshop Space, 4th Floor - 300 Ouellette Ave., School of Computer Science Advanced Computing Hub
Deep Learning Models use deep neural networks to perform Link Prediction. Neural Networks learn parameters such as weights and biases and combine them with the input data to recognize significant patterns. Deep networks organize parameters into separate layers, generally interspersed with non-linear activation functions. More advanced layers perform more complex operations, such as convolutional layers that learn convolution kernels to apply to the input data or recurrent layers that recursively handle sequential inputs. In the LP field, KG embeddings are usually learned jointly with the weights and biases of the layers. These shared parameters make these models more expressive but potentially longer to train and more prone to overfitting. There are three groups in this family, based on the neural architecture they employ: (i) Convolutional Neural Networks, (ii) Capsule Neural Networks, and (iii) Recurrent Neural Networks (RNNs).
- What are Deep learning models for KG embeddings
- (i) Convolutional Neural Networks,
- ConvE (Convolutional Knowledge Graph Embeddings)
- ConvKB (Convolutional Neural Networks for Knowledge Base Embeddings)
- ConvR (Convolutional Residual)
- InteractE
- (ii) Capsule Neural Networks
- CapsE (Capsule Networks for Knowledge Graph Embeddings)
- (iii) Recurrent Neural Networks (RNNs)
- Recurring Skipping Networks (RSNs)
- Advantages, Disadvantages and Limitations
- Basic understanding of neural networks
- Basic understanding of Embeddings
Amangel Bhullar is a Ph.D. candidate in Computer Science at the University of Windsor, specializing in artificial intelligence with a focus on knowledge representation, machine learning, Social networks, and knowledge graphs. She currently serves as the President of the Graduate Student Society (GSS), where she leads initiatives to enhance the academic and social experience of graduate students.
In addition to her role at GSS, Amangel is the Director of the Lancer Sport and Recreation Center (LSRC) Corporation and serves as a Member of the Board of Governors at the University of Windsor. Her leadership contributions extend further as an Ex-Officio Member of the University Senate, where she brings a student-centred perspective to university policy and governance matters.