Search Results for author: Jonathan Heek

Found 10 papers, 5 papers with code

Multistep Consistency Models

no code implementations11 Mar 2024 Jonathan Heek, Emiel Hoogeboom, Tim Salimans

By increasing the sample budget from a single step to 2-8 steps, we can train models more easily that generate higher quality samples, while retaining much of the sampling speed benefits.

Rolling Diffusion Models

no code implementations12 Feb 2024 David Ruhe, Jonathan Heek, Tim Salimans, Emiel Hoogeboom

Diffusion models have recently been increasingly applied to temporal data such as video, fluid mechanics simulations, or climate data.

Denoising Video Prediction

Efficiently Scaling Transformer Inference

no code implementations9 Nov 2022 Reiner Pope, Sholto Douglas, Aakanksha Chowdhery, Jacob Devlin, James Bradbury, Anselm Levskaya, Jonathan Heek, Kefan Xiao, Shivani Agrawal, Jeff Dean

We study the problem of efficient generative inference for Transformer models, in one of its most challenging settings: large deep models, with tight latency targets and long sequence lengths.


Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks

2 code implementations14 Nov 2021 Lasse Espeholt, Shreya Agrawal, Casper Sønderby, Manoj Kumar, Jonathan Heek, Carla Bromberg, Cenk Gazen, Jason Hickey, Aaron Bell, Nal Kalchbrenner

An emerging class of weather models based on neural networks represents a paradigm shift in weather forecasting: the models learn the required transformations from data instead of relying on hand-coded physics and are computationally efficient.

energy management Management +2

Bayesian Inference for Large Scale Image Classification

no code implementations9 Aug 2019 Jonathan Heek, Nal Kalchbrenner

We show that ATMC is intrinsically robust to overfitting on the training data and that ATMC provides a better calibrated measure of uncertainty compared to the optimization baseline.

Bayesian Inference Classification +4

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