46 citations · 215 across the 26 of their papers we have counts for
5 papers · 1 filter
Plankton-FL: Exploration of Federated Learning for Privacy-Preserving Training of Deep Neural Networks for Phytoplankton Classification
Daniel Zhang, Vikram Voleti, Alexander Wong +1
Creating high-performance generalizable deep neural networks for phytoplankton monitoring requires utilizing large-scale data coming from diverse global water sources. A major chal…
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…
SMPL-IK: Learned Morphology-Aware Inverse Kinematics for AI Driven Artistic Workflows
Vikram Voleti, Boris N. Oreshkin, Florent Bocquelet +3
Inverse Kinematics (IK) systems are often rigid with respect to their input character, thus requiring user intervention to be adapted to new skeletons. In this paper we aim at crea…
Towards Generating Large Synthetic Phytoplankton Datasets for Efficient Monitoring of Harmful Algal Blooms
Nitpreet Bamra, Vikram Voleti, Alexander Wong +1
Climate change is increasing the frequency and severity of harmful algal blooms (HABs), which cause significant fish deaths in aquaculture farms. This contributes to ocean pollutio…
MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation
Vikram Voleti, Alexia Jolicoeur-Martineau, Christopher Pal
Video prediction is a challenging task. The quality of video frames from current state-of-the-art (SOTA) generative models tends to be poor and generalization beyond the training d…