4 papers
On Correctness of Automatic Differentiation for Non-Differentiable Functions
Wonyeol Lee, Hangyeol Yu, Xavier Rival +1
Differentiation lies at the core of many machine-learning algorithms, and is well-supported by popular autodiff systems, such as TensorFlow and PyTorch. Originally, these systems h…
Differentiable Algorithm for Marginalising Changepoints
Hyoungjin Lim, Gwonsoo Che, Wonyeol Lee +1
We present an algorithm for marginalising changepoints in time-series models that assume a fixed number of unknown changepoints. Our algorithm is differentiable with respect to its…
Towards Verified Stochastic Variational Inference for Probabilistic Programs
Wonyeol Lee, Hangyeol Yu, Xavier Rival +1
Probabilistic programming is the idea of writing models from statistics and machine learning using program notations and reasoning about these models using generic inference engine…
Reparameterization Gradient for Non-differentiable Models
Wonyeol Lee, Hangyeol Yu, Hongseok Yang
We present a new algorithm for stochastic variational inference that targets at models with non-differentiable densities. One of the key challenges in stochastic variational infere…