4 papers
Diffusion Models Observe Only Gradients: A Geometric Perspective on Score Matching Errors
Naïl B. Khelifa, Richard E. Turner, Ramji Venkataramanan
Score-based diffusion models are typically trained by minimizing the score matching error, and standard theoretical analyses rely on this quantity to bound the sampling discr…
Probabilistic Retrofitting of Learned Simulators
Cristiana Diaconu, Miles Cranmer, Richard E. Turner +2
Dominant approaches for modelling Partial Differential Equations (PDEs) rely on deterministic predictions, yet many physical systems of interest are inherently chaotic and uncertai…
Recursively Trained Diffusion Models: Limiting Collapse Distribution and Spectral Characterization
Naïl B. Khelifa, Richard E. Turner, Ramji Venkataramanan
Recursive training of generative models on their own outputs can lead to model collapse, a compounding drift away from the true data distribution. Existing theoretical works bound…
Fearless Stochasticity in Expectation Propagation
Jonathan So, Richard E. Turner
Expectation propagation (EP) is a family of algorithms for performing approximate inference in probabilistic models. The updates of EP involve the evaluation of moments -- expectat…