Probabilistic Programming and Inference Algorithms Publication Trend The graph below shows the total number of publications each year in Probabilistic Programming and Inference Algorithms.

We demonstrate its applicability by considering the min-cost flow problem, by giving a novel algorithm for linear programming over unimodular spaces, and by providing a different proof that for ...

He is the author of the multi-volume work, the magnum opus, The Art of Computer Programming. He made several key contributions to the rigorous analysis of the computational complexity of algorithms.

Unlike dynamic programming approaches whose performance relies heavily on the degree of discretization applied to the data, our algorithm does not suffer from such space-complexity issues.

Getting to the heart of causality is central to understanding the world around us. What causes one variable—be it a biological species, a voting region, a company stock, or a local climate—to shift ...

Research from all publishers Recent work in probabilistic programming has sought to address both theoretical and computational challenges. For example, investigations into the intrinsic complexity ...