9 citations · 9 across the 1 of their papers we have counts for
5 papers
ModelHub.AI: Dissemination Platform for Deep Learning Models
Ahmed Hosny, Michael Schwier, Christoph Berger +13
Recent advances in artificial intelligence research have led to a profusion of studies that apply deep learning to problems in image analysis and natural language processing among…
Exploring Self-Supervised Regularization for Supervised and Semi-Supervised Learning
Phi Vu Tran
Recent advances in semi-supervised learning have shown tremendous potential in overcoming a major barrier to the success of modern machine learning algorithms: access to vast amoun…
Multi-Task Graph Autoencoders
Phi Vu Tran
We examine two fundamental tasks associated with graph representation learning: link prediction and node classification. We present a new autoencoder architecture capable of learni…
Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning
David Mascharka, Philip Tran, Ryan Soklaski +1
Visual question answering requires high-order reasoning about an image, which is a fundamental capability needed by machine systems to follow complex directives. Recently, modular…
Learning to Make Predictions on Graphs with Autoencoders
Phi Vu Tran
We examine two fundamental tasks associated with graph representation learning: link prediction and semi-supervised node classification. We present a novel autoencoder architecture…