Talk: Building Machines that Imagine and Reason 2

Talk: Building Machines that Imagine and Reason
I am excited to be one the speakers at this year's Deep Learning Summer School in Montreal on the 6th August 2016. Slides can be found here: slides link. And the abstract is below. Building Machines that Imagine and Reason: Principles and Applications of Deep Generative Models Deep generative models provide a solution to the problem of unsupervised ...

Learning in Brains and Machines (4): Episodic and Interactive Memory

Learning in Brains and Machines (4): Episodic and Interactive Memory
· Read in · 2080 words · All posts in series  · memory, like yours, exerts a powerful influence over my interaction with the world. It is reconstructive and evocative; I can easily form an image of hot December days in the South African summer, and remember my first time—it was morning on an Easter Sunday in April a few years ago—that I saw and felt snow. My ...

A Year of Approximate Inference: Review of the NIPS 2015 Workshop 3

A Year of Approximate Inference: Review of the NIPS 2015 Workshop
inference lies no longer at the fringe. The importance of how we connect our observed data to the assumptions made by our statistical models—the task of inference—was a central part of this year's Neural Information Processing Systems (NIPS) conference: Zoubin Ghahramani's opening keynote set the stage and the pageant of inference included forecasting, compression, decision making, personalised modelling, and automating the ...

Machine Learning Trick of the Day (6): Tricks with Sticks 2

Machine Learning Trick of the Day (6): Tricks with Sticks
· Read in  · Our first encounters with probability are often through a collection of simple games. The games of probability are played with coins, dice, cards, balls and urns, and sticks and strings. Using these games, we built an intuition that allows us to reason and act in ways that account for randomness in the world. But ...

Bayesian Reasoning and Deep Learning 4

Bayesian Reasoning and Deep Learning
I gave a talk entitled 'Bayesian Reasoning and Deep Learning' recently. Here is the abstract and the slides for interest. Slides Bayesian Reasoning and Deep Learning Abstract Deep learning and Bayesian machine learning are currently two of the most active areas of machine learning research. Deep learning provides a powerful class of models and an ...

Machine Learning Trick of the Day (1): Replica Trick 3

'Tricks' of all sorts are used throughout machine learning, in both research and in production settings. These tricks allow us to address many different types of data analysis problems, being roughly of either an analytical, statistical, algorithmic, or numerical flavour. Today's trick is in the analytical class and comes to us from statistical physics: the popular Replica trick. The replica ...

A Statistical View of Deep Learning: Retrospective 1

A Statistical View of Deep Learning: Retrospective
Over the past 6 months, I've taken to writing a series of posts (one each month) on a statistical view of deep learning with two principal motivations in mind. The first was as a personal exercise to make concrete and to test the limits of the way that I think about, and use deep learning in my every ...