46 citations · 215 across the 26 of their papers we have counts for
8 papers · 1 filter
Generative Models of Brain Dynamics -- A review
Mahta Ramezanian Panahi, Germán Abrevaya, Jean-Christophe Gagnon-Audet +3
The principled design and discovery of biologically- and physically-informed models of neuronal dynamics has been advancing since the mid-twentieth century. Recent developments in…
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…
FairCal: Fairness Calibration for Face Verification
Tiago Salvador, Stephanie Cairns, Vikram Voleti +2
Despite being widely used, face recognition models suffer from bias: the probability of a false positive (incorrect face match) strongly depends on sensitive attributes such as the…
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…
Accounting for Variance in Machine Learning Benchmarks
Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi +14
Strong empirical evidence that one machine-learning algorithm A outperforms another one B ideally calls for multiple trials optimizing the learning pipeline over sources of variati…