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We explore the downstream task performances for graph neural network (GNN) self-supervised learning (SSL) methods trained on subgraphs …
Synthetic image generation has recently experienced significant improvements in domains such as natural image or art generation. …
Robots in many real-world settings have access to force/torque sensors in their gripper and tactile sensing is often necessary in tasks …
We present Azimuth, an open-source and easy-to-use tool to perform error analysis for text classification. Compared to other stages of …
Structured knowledge grounding (SKG) leverages structured knowledge to complete user requests, such as semantic parsing over databases …
Recent extensions of Cellular Automata (CA) have incorporated key ideas from modern deep learning, dramatically extending their …
Video prediction is a challenging task. The quality of video frames from current state-of-the-art (SOTA) generative models tends to be …
Recent work has seen the development of general purpose neural architectures that can be trained to perform tasks across diverse data …
We study the generalisation properties of majority voting on finite ensembles of classifiers, proving margin-based generalisation …
Semantic segmentation is a popular task that has piqued the interest of many industries and research communities. However, acquiring …