ExIt-OOS: Towards Learning from Planning in Imperfect Information Games

no code implementations • 30 Aug 2018 • Andy Kitchen, Michela Benedetti

The current state of the art in playing many important perfect information games, including Chess and Go, combines planning and deep reinforcement learning with self-play.

reinforcement-learning Reinforcement Learning (RL)

Generative Visual Rationales

no code implementations • 4 Apr 2018 • Jarrel Seah, Jennifer Tang, Andy Kitchen, Jonathan Seah

For each prediction, we generate visual rationales by optimizing a latent representation to minimize the prediction of disease while constrained by a similarity measure in image space.

Thinking like a machine — generating visual rationales through latent space optimization

no code implementations • ICLR 2018 • Jarrel Seah, Jennifer Tang, Andy Kitchen, Jonathan Seah

For each prediction, we generate visual rationales for positive classifications by optimizing a latent representation to minimize the probability of disease while constrained by a similarity measure in image space.

Deep Generative Adversarial Neural Networks for Realistic Prostate Lesion MRI Synthesis

no code implementations • 1 Aug 2017 • Andy Kitchen, Jarrel Seah

Generative Adversarial Neural Networks (GANs) are applied to the synthetic generation of prostate lesion MRI images.