Exploring the Lottery Ticket Hypothesis

Pruning is a well known Machine Learning technique in which unnecessary weights are removed from a neural network model after training. In some cases, pruning can reduce model sizes by more than 90% without compromising on model accuracy while potentially offering a significant reduction in inference memory usage (see some great examples here). In 2018, […]

Attention Augmented Convolutional Networks

Convolutional neural networks have proven to be a powerful tool for image recognition, allowing for ever-improving results in image classification (ImageNet), object detection (COCO), and other tasks. Despite their success, convolutions are limited by their locality, i.e. their inability to consider relations between different areas of an image. On the other hand, a popular mechanism […]

TossingBot – Teaching Robots to Throw Objects Accurately

One of the most well-known challenges in robotics is ‘picking’, i.e. using a robotic claw to lift a single object, usually from a cluttered 3-dimensional pile of objects. Picking an object from a pile and moving it to a destination can be a useful capability in many real-world situations but human experience shows that in […]