80 citations · 139 across the 6 of their papers we have counts for
7 papers
Phenaki: Variable Length Video Generation From Open Domain Textual Description
Ruben Villegas, Mohammad Babaeizadeh, Pieter-Jan Kindermans +6
We present Phenaki, a model capable of realistic video synthesis, given a sequence of textual prompts. Generating videos from text is particularly challenging due to the computatio…
Adaptive Optimization with Examplewise Gradients
Julius Kunze, James Townsend, David Barber
We propose a new, more general approach to the design of stochastic gradient-based optimization methods for machine learning. In this new framework, optimizers assume access to a b…
HiLLoC: Lossless Image Compression with Hierarchical Latent Variable Models
James Townsend, Thomas Bird, Julius Kunze +1
We make the following striking observation: fully convolutional VAE models trained on 32x32 ImageNet can generalize well, not just to 64x64 but also to far larger photographs, with…
Gaussian Mean Field Regularizes by Limiting Learned Information
Julius Kunze, Louis Kirsch, Hippolyt Ritter +1
Variational inference with a factorized Gaussian posterior estimate is a widely used approach for learning parameters and hidden variables. Empirically, a regularizing effect can b…
Modular Networks: Learning to Decompose Neural Computation
Louis Kirsch, Julius Kunze, David Barber
Scaling model capacity has been vital in the success of deep learning. For a typical network, necessary compute resources and training time grow dramatically with model size. Condi…
Stochastic Variational Optimization
Thomas Bird, Julius Kunze, David Barber
Variational Optimization forms a differentiable upper bound on an objective. We show that approaches such as Natural Evolution Strategies and Gaussian Perturbation, are special cas…
Transfer Learning for Speech Recognition on a Budget
Julius Kunze, Louis Kirsch, Ilia Kurenkov +3
End-to-end training of automated speech recognition (ASR) systems requires massive data and compute resources. We explore transfer learning based on model adaptation as an approach…