4 papers
Temporal Variational Implicit Neural Representations
Batuhan Koyuncu, Rachael DeVries, Ole Winther +1
We introduce Temporal Variational Implicit Neural Representations (TV-INRs), a probabilistic framework for modeling irregular multivariate time series that enables efficient and ac…
Hyper-Transforming Latent Diffusion Models
Ignacio Peis, Batuhan Koyuncu, Isabel Valera +1
We introduce a novel generative framework for functions by integrating Implicit Neural Representations (INRs) and Transformer-based hypernetworks into latent variable models. Unlik…
Variational Mixture of HyperGenerators for Learning Distributions Over Functions
Batuhan Koyuncu, Pablo Sanchez-Martin, Ignacio Peis +2
Recent approaches build on implicit neural representations (INRs) to propose generative models over function spaces. However, they are computationally costly when dealing with infe…
Analysis of ODE2VAE with Examples
Batuhan Koyuncu
Deep generative models aim to learn underlying distributions that generate the observed data. Given the fact that the generative distribution may be complex and intractable, deep l…