98 citations · 216 across the 13 of their papers we have counts for
7 papers · 1 filter
A Fourier Space Perspective on Diffusion Models
Fabian Falck, Teodora Pandeva, Kiarash Zahirnia +5
Diffusion models are state-of-the-art generative models on data modalities such as images, audio, proteins and materials. These modalities share the property of exponentially decay…
Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations
Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin +2
End-to-end learning of dynamical systems with black-box models, such as neural ordinary differential equations (ODEs), provides a flexible framework for learning dynamics from data…
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems
Geoffrey Roeder, Paul K. Grant, Andrew Phillips +2
We introduce a flexible, scalable Bayesian inference framework for nonlinear dynamical systems characterised by distinct and hierarchical variability at the individual, group, and…
Soft Weight-Sharing for Neural Network Compression
Karen Ullrich, Edward Meeds, Max Welling
The success of deep learning in numerous application domains created the de- sire to run and train them on mobile devices. This however, conflicts with their computationally, memor…
Automatic Variational ABC
Alexander Moreno, Tameem Adel, Edward Meeds +2
Approximate Bayesian Computation (ABC) is a framework for performing likelihood-free posterior inference for simulation models. Stochastic Variational inference (SVI) is an appeali…
Hamiltonian ABC
Edward Meeds, Robert Leenders, Max Welling
Approximate Bayesian computation (ABC) is a powerful and elegant framework for performing inference in simulation-based models. However, due to the difficulty in scaling likelihood…
POPE: Post Optimization Posterior Evaluation of Likelihood Free Models
Edward Meeds, Michael Chiang, Mary Lee +3
In many domains, scientists build complex simulators of natural phenomena that encode their hypotheses about the underlying processes. These simulators can be deterministic or stoc…