6.1k citations · 6.5k across the 16 of their papers we have counts for
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Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting
Kashif Rasul, Calvin Seward, Ingmar Schuster +1
In this work, we propose \texttt{TimeGrad}, an autoregressive model for multivariate probabilistic time series forecasting which samples from the data distribution at each time ste…
Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows
Kashif Rasul, Abdul-Saboor Sheikh, Ingmar Schuster +2
Time series forecasting is often fundamental to scientific and engineering problems and enables decision making. With ever increasing data set sizes, a trivial solution to scale up…
Set Flow: A Permutation Invariant Normalizing Flow
Kashif Rasul, Ingmar Schuster, Roland Vollgraf +1
We present a generative model that is defined on finite sets of exchangeable, potentially high dimensional, data. As the architecture is an extension of RealNVPs, it inherits all i…
A Deep Learning System for Predicting Size and Fit in Fashion E-Commerce
Abdul-Saboor Sheikh, Romain Guigoures, Evgenii Koriagin +4
Personalized size and fit recommendations bear crucial significance for any fashion e-commerce platform. Predicting the correct fit drives customer satisfaction and benefits the bu…
Learning Set-equivariant Functions with SWARM Mappings
Roland Vollgraf
In this work we propose a new neural network architecture that efficiently implements and learns general purpose set-equivariant functions. Such a function f maps a set of entities…
A Bandit Framework for Optimal Selection of Reinforcement Learning Agents
Andreas Merentitis, Kashif Rasul, Roland Vollgraf +2
Deep Reinforcement Learning has been shown to be very successful in complex games, e.g. Atari or Go. These games have clearly defined rules, and hence allow simulation. In many pra…
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao, Kashif Rasul, Roland Vollgraf
We present Fashion-MNIST, a new dataset comprising of 28x28 grayscale images of 70,000 fashion products from 10 categories, with 7,000 images per category. The training set has 60,…