365 citations · 840 across the 6 of their papers we have counts for
12 papers
Gradual Domain Adaptation in the Wild:When Intermediate Distributions are Absent
Samira Abnar, Rianne van den Berg, Golnaz Ghiasi +3
We focus on the problem of domain adaptation when the goal is shifting the model towards the target distribution, rather than learning domain invariant representations. It has been…
Colorization Transformer
Manoj Kumar, Dirk Weissenborn, Nal Kalchbrenner
We present the Colorization Transformer, a novel approach for diverse high fidelity image colorization based on self-attention. Given a grayscale image, the colorization proceeds i…
Towards Causal Representation Learning
Bernhard Schölkopf, Francesco Locatello, Stefan Bauer +4
The two fields of machine learning and graphical causality arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to benefit…
A Spectral Energy Distance for Parallel Speech Synthesis
Alexey A. Gritsenko, Tim Salimans, Rianne van den Berg +2
Speech synthesis is an important practical generative modeling problem that has seen great progress over the last few years, with likelihood-based autoregressive neural models now…
MetNet: A Neural Weather Model for Precipitation Forecasting
Casper Kaae Sønderby, Lasse Espeholt, Jonathan Heek +6
Weather forecasting is a long standing scientific challenge with direct social and economic impact. The task is suitable for deep neural networks due to vast amounts of continuousl…
Axial Attention in Multidimensional Transformers
Jonathan Ho, Nal Kalchbrenner, Dirk Weissenborn +1
We propose Axial Transformers, a self-attention-based autoregressive model for images and other data organized as high dimensional tensors. Existing autoregressive models either su…