Artificial Intelligence and Machine Learning in Cambridge 2017
This academic workshop aims to connect this community better and to learn from each other about interesting research and applications in the broad machine learning spectrum.
Grammar Variational Autoencoder
Deep generative models have been wildly successful at learning coherent latent representations for continuous data such as video and audio. However, generative modeling of discrete data such as arithmetic expressions and molecular structures still poses…
IMMERSIVE SENSORY VR SYSTEM
This is one of the finalists from the Microsoft STEM Student Challenge. The Challenge was open to UK students in years 8-10. They were asked to come up with technology idea that could exist in 2037…
Machine Learning for Embodied Design in Virtual Reality
Much of my research has tried to create virtual characters that are able to interact with real people via body language in immersive virtual reality. While some very simple models can create impressive effects and…
Teaching AI to make decisions and communicate
The term ‘Artificial Intelligence’ may have been coined way back in the 1950s, but we have yet to see the types of machines described in books and films. In our daily lives and workplaces, we…
FATE: Fairness, Accountability, Transparency & Ethics in AI
We study the complex societal implications of artificial intelligence (AI), machine learning (ML), and natural language processing (NLP). Our aim is to facilitate computational techniques that are both innovative and responsible, while prioritizing issues of…