**Learning Energy-Based Models
of
High-Dimensional Data**

**Discovering causal structure
as a goal for unsupervised learning**

**A different kind of hidden
structure**

**A trade-off between how well
the model fits the data and the tractability of inference**

**Energy-Based Models with
deterministic hidden units**

**Maximum likelihood learning
is hard**

**Backpropagation can compute
the gradient that Hybrid Monte Carlo needs**

**The online HMC learning
procedure**

**Frequently Approximately
Satisfied constraints**

**Learning constraints from
natural images
(Yee-Whye Teh)**