43 citations · 94 across the 7 of their papers we have counts for
9 papers
Score-based Denoising Diffusion with Non-Isotropic Gaussian Noise Models
Vikram Voleti, Christopher Pal, Adam Oberman
Generative models based on denoising diffusion techniques have led to an unprecedented increase in the quality and diversity of imagery that is now possible to create with neural g…
Simple Video Generation using Neural ODEs
David Kanaa, Vikram Voleti, Samira Ebrahimi Kahou +1
Despite having been studied to a great extent, the task of conditional generation of sequences of frames, or videos, remains extremely challenging. It is a common belief that a key…
SALT: Sea lice Adaptive Lattice Tracking -- An Unsupervised Approach to Generate an Improved Ocean Model
Ju An Park, Vikram Voleti, Kathryn E. Thomas +2
Warming oceans due to climate change are leading to increased numbers of ectoparasitic copepods, also known as sea lice, which can cause significant ecological loss to wild salmon…
Multi-Resolution Continuous Normalizing Flows
Vikram Voleti, Chris Finlay, Adam Oberman +1
Recent work has shown that Neural Ordinary Differential Equations (ODEs) can serve as generative models of images using the perspective of Continuous Normalizing Flows (CNFs). Such…
Frustratingly Easy Uncertainty Estimation for Distribution Shift
Tiago Salvador, Vikram Voleti, Alexander Iannantuono +1
Distribution shift is an important concern in deep image classification, produced either by corruption of the source images, or a complete change, with the solution involving domai…
gradSim: Differentiable simulation for system identification and visuomotor control
Krishna Murthy Jatavallabhula, Miles Macklin, Florian Golemo +11
We consider the problem of estimating an object's physical properties such as mass, friction, and elasticity directly from video sequences. Such a system identification problem is…