2.7k citations · 4k across the 68 of their papers we have counts for
9 papers · 1 filter
Building LEGO Using Deep Generative Models of Graphs
Rylee Thompson, Elahe Ghalebi, Terrance DeVries +1
Generative models are now used to create a variety of high-quality digital artifacts. Yet their use in designing physical objects has received far less attention. In this paper, we…
Evaluating Curriculum Learning Strategies in Neural Combinatorial Optimization
Michal Lisicki, Arash Afkanpour, Graham W. Taylor
Neural combinatorial optimization (NCO) aims at designing problem-independent and efficient neural network-based strategies for solving combinatorial problems. The field recently e…
Neuron-based explanations of neural networks sacrifice completeness and interpretability
Nolan Dey, Eric Taylor, Alexander Wong +2
High quality explanations of neural networks (NNs) should exhibit two key properties. Completeness ensures that they accurately reflect a network's function and interpretability ma…
Instance Selection for GANs
Terrance DeVries, Michal Drozdzal, Graham W. Taylor
Recent advances in Generative Adversarial Networks (GANs) have led to their widespread adoption for the purposes of generating high quality synthetic imagery. While capable of gene…
Generative Compositional Augmentations for Scene Graph Prediction
Boris Knyazev, Harm de Vries, Cătălina Cangea +3
Inferring objects and their relationships from an image in the form of a scene graph is useful in many applications at the intersection of vision and language. We consider a challe…
Enabling Continual Learning with Differentiable Hebbian Plasticity
Vithursan Thangarasa, Thomas Miconi, Graham W. Taylor
Continual learning is the problem of sequentially learning new tasks or knowledge while protecting previously acquired knowledge. However, catastrophic forgetting poses a grand cha…
Graph Density-Aware Losses for Novel Compositions in Scene Graph Generation
Boris Knyazev, Harm de Vries, Cătălina Cangea +3
Scene graph generation (SGG) aims to predict graph-structured descriptions of input images, in the form of objects and relationships between them. This task is becoming increasingl…
Sample-Efficient Model-based Actor-Critic for an Interactive Dialogue Task
Katya Kudashkina, Valliappa Chockalingam, Graham W. Taylor +1
Human-computer interactive systems that rely on machine learning are becoming paramount to the lives of millions of people who use digital assistants on a daily basis. Yet, further…
ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis
Eu Wern Teh, Terrance DeVries, Graham W. Taylor
We consider the problem of distance metric learning (DML), where the task is to learn an effective similarity measure between images. We revisit ProxyNCA and incorporate several en…