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10/16/2022
Semantic Segmentation with Active Semi-Supervised Representation Learning
Obtaining human per-pixel labels for semantic segmentation is incredibly...
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03/21/2022
Semantic Segmentation with Active Semi-Supervised Learning
Using deep learning, we now have the ability to create exceptionally goo...
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06/07/2021
Launchpad: A Programming Model for Distributed Machine Learning Research
A major driver behind the success of modern machine learning algorithms ...
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03/17/2021
Regularized Behavior Value Estimation
Offline reinforcement learning restricts the learning process to rely on...
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03/09/2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport
Hamiltonian Monte Carlo is a powerful algorithm for sampling from diffic...
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11/05/2018
Simple, Distributed, and Accelerated Probabilistic Programming
We describe a simple, low-level approach for embedding probabilistic pro...
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12/23/2017
Aerial Spectral Super-Resolution using Conditional Adversarial Networks
Inferring spectral signatures from ground based natural images has acqui...
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11/15/2017
Latent Constraints: Learning to Generate Conditionally from Unconditional Generative Models
Deep generative neural networks have proven effective at both conditiona...
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10/17/2017
On the challenges of learning with inference networks on sparse, high-dimensional data
We study parameter estimation in Nonlinear Factor Analysis (NFA) where t...
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02/20/2016
The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM
We propose the segmented iHMM (siHMM), a hierarchical infinite hidden Ma...
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12/21/2014
