3.6k citations · 6.2k across the 27 of their papers we have counts for
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Introduction to Stochastic Differential Equations for Generative Machine Learning: A Variational Perspective
Ole Winther, Paul Jeha, Sander Dieleman +3
The use of ordinary and stochastic differential equations has led to substantial progress in generative machine learning with applications to, for example, image, video and biomole…
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC
Yilun Du, Conor Durkan, Robin Strudel +6
Since their introduction, diffusion models have quickly become the prevailing approach to generative modeling in many domains. They can be interpreted as learning the gradients of…
Categorical SDEs with Simplex Diffusion
Pierre H. Richemond, Sander Dieleman, Arnaud Doucet
Diffusion models typically operate in the standard framework of generative modelling by producing continuously-valued datapoints. To this end, they rely on a progressive Gaussian s…
General-purpose, long-context autoregressive modeling with Perceiver AR
Curtis Hawthorne, Andrew Jaegle, Cătălina Cangea +12
Real-world data is high-dimensional: a book, image, or musical performance can easily contain hundreds of thousands of elements even after compression. However, the most commonly u…
Variable-rate discrete representation learning
Sander Dieleman, Charlie Nash, Jesse Engel +1
Semantically meaningful information content in perceptual signals is usually unevenly distributed. In speech signals for example, there are often many silences, and the speed of pr…
Towards transformation-resilient provenance detection of digital media
Jamie Hayes, Krishnamurthy, Dvijotham +4
Advancements in deep generative models have made it possible to synthesize images, videos and audio signals that are difficult to distinguish from natural signals, creating opportu…
Piano Genie
Chris Donahue, Ian Simon, Sander Dieleman
We present Piano Genie, an intelligent controller which allows non-musicians to improvise on the piano. With Piano Genie, a user performs on a simple interface with eight buttons,…
Parallel WaveNet: Fast High-Fidelity Speech Synthesis
Aaron van den Oord, Yazhe Li, Igor Babuschkin +19
The recently-developed WaveNet architecture is the current state of the art in realistic speech synthesis, consistently rated as more natural sounding for many different languages…
Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders
Jesse Engel, Cinjon Resnick, Adam Roberts +4
Generative models in vision have seen rapid progress due to algorithmic improvements and the availability of high-quality image datasets. In this paper, we offer contributions in b…
Exploiting Cyclic Symmetry in Convolutional Neural Networks
Sander Dieleman, Jeffrey De Fauw, Koray Kavukcuoglu
Many classes of images exhibit rotational symmetry. Convolutional neural networks are sometimes trained using data augmentation to exploit this, but they are still required to lear…