Learning from One Continuous Video Stream

no code implementations • 1 Dec 2023 • João Carreira, Michael King, Viorica Pătrăucean, Dilara Gokay, Cătălin Ionescu, Yi Yang, Daniel Zoran, Joseph Heyward, Carl Doersch, Yusuf Aytar, Dima Damen, Andrew Zisserman

We introduce a framework for online learning from a single continuous video stream -- the way people and animals learn, without mini-batches, data augmentation or shuffling.

Data Augmentation Future prediction

Learning to estimate a surrogate respiratory signal from cardiac motion by signal-to-signal translation

no code implementations • 20 Jul 2022 • Akshay Iyer, Clifford Lindsay, Hendrik Pretorius, Michael King

Our goal is to lay a foundation to guide the optimization of neural networks for respiratory motion correction from SPECT without the need for an EMT.

Alchemy: A benchmark and analysis toolkit for meta-reinforcement learning agents

1 code implementation • 4 Feb 2021 • Jane X. Wang, Michael King, Nicolas Porcel, Zeb Kurth-Nelson, Tina Zhu, Charlie Deck, Peter Choy, Mary Cassin, Malcolm Reynolds, Francis Song, Gavin Buttimore, David P. Reichert, Neil Rabinowitz, Loic Matthey, Demis Hassabis, Alexander Lerchner, Matthew Botvinick

There has been rapidly growing interest in meta-learning as a method for increasing the flexibility and sample efficiency of reinforcement learning.

Meta-Learning Meta Reinforcement Learning +3

The Criminality From Face Illusion

no code implementations • 6 Jun 2020 • Kevin W. Bowyer, Michael King, Walter Scheirer, Kushal Vangara

A few recent publications have claimed success in analyzing an image of a person's face in order to predict the person's status as Criminal / Non-Criminal.

Experimental Design