BAIR Blog Post on Depth Maps and Deep Learning in Robotics

As usual, I have been slow blogging here. This time, I have a valid excuse. I was consumed with writing for another one: the Berkeley Artificial Intelligence Research (BAIR) blog, of which I serve as the primary editorial board member. If I may put my non-existent ego aside, the BAIR blog is more important (and popular!)¹ than my personal blog. BAIR blog posts generally require more effort to write than personal blog posts. Quality over quantity, right?

You can read my blog post there, which is about using depth images in the context of deep learning and robotics. Unlike most BAIR blog posts, this one tries to describe a little history and a unifying theme (depth images) across multiple papers. It’s a little long; we put in a lot of effort into this post.

I also have an earlier BAIR blog post from last year, about the work I did with Markov chain Monte Carlo methods. I’ve since moved on to robotics research, which explains the sudden change in blogging topics.

Thank you for reading this little note, and I hope you also enjoy the BAIR blog post.