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Matthew Hoffman

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Scalable Spatiotemporal Prediction with Bayesian Neural Fields

Mar 12, 2024
Feras Saad, Jacob Burnim, Colin Carroll, Brian Patton, Urs Köster, Rif A. Saurous, Matthew Hoffman

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Semantic Segmentation with Active Semi-Supervised Representation Learning

Oct 16, 2022
Aneesh Rangnekar, Christopher Kanan, Matthew Hoffman

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Semantic Segmentation with Active Semi-Supervised Learning

Mar 21, 2022
Aneesh Rangnekar, Christopher Kanan, Matthew Hoffman

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Launchpad: A Programming Model for Distributed Machine Learning Research

Jun 07, 2021
Fan Yang, Gabriel Barth-Maron, Piotr Stańczyk, Matthew Hoffman, Siqi Liu, Manuel Kroiss, Aedan Pope, Alban Rrustemi

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Regularized Behavior Value Estimation

Mar 17, 2021
Caglar Gulcehre, Sergio Gómez Colmenarejo, Ziyu Wang, Jakub Sygnowski, Thomas Paine, Konrad Zolna, Yutian Chen, Matthew Hoffman, Razvan Pascanu, Nando de Freitas

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NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport

Mar 09, 2019
Matthew Hoffman, Pavel Sountsov, Joshua V. Dillon, Ian Langmore, Dustin Tran, Srinivas Vasudevan

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Simple, Distributed, and Accelerated Probabilistic Programming

Nov 29, 2018
Dustin Tran, Matthew Hoffman, Dave Moore, Christopher Suter, Srinivas Vasudevan, Alexey Radul, Matthew Johnson, Rif A. Saurous

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Aerial Spectral Super-Resolution using Conditional Adversarial Networks

Dec 23, 2017
Aneesh Rangnekar, Nilay Mokashi, Emmett Ientilucci, Christopher Kanan, Matthew Hoffman

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Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models

Dec 21, 2017
Jesse Engel, Matthew Hoffman, Adam Roberts

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