Probably actually reading



Stuff that I am currently actively reading. If you are looking at this, and you aren’t me, you should really be re-evaluating your hobbies.

See also my more aspirational paper reading list.

SDEs in optimisation and learning

To explore: Gradient flows gradient flow.

Nguyen and Malinsky (2020)

Statistical Inference via Convex Optimization.

Conjugate functions illustrated.

Francis Bach on the use of geometric sums and a different take by Julyan Arbel.

Tutorial to approximating differentiable control problems. An extension of this is universal differential equations.

SDEs

General emulation

Sensitivity Analysis

References

Nguyen, Long, and Andy Malinsky. 2020. “Exploration and Implementation of Neural Ordinary Differential Equations,” 34.

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