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11/14/2022
Treatment-RSPN: Recurrent Sum-Product Networks for Sequential Treatment Regimes
Sum-product networks (SPNs) have recently emerged as a novel deep learni...
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02/10/2019
Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion
The predictive performance of supervised learning algorithms depends on ...
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04/17/2017
Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models
Professional-grade software applications are powerful but complicated-ex...
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06/08/2016
Deep Successor Reinforcement Learning
Learning robust value functions given raw observations and rewards is no...
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04/20/2016
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation
Learning goal-directed behavior in environments with sparse feedback is ...
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04/01/2016
Nonparametric Spherical Topic Modeling with Word Embeddings
Traditional topic models do not account for semantic regularities in lan...
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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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05/31/2015
Automatic Inference for Inverting Software Simulators via Probabilistic Programming
Models of complex systems are often formalized as sequential software si...
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03/01/2015
JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes
Markov jump processes (MJPs) are used to model a wide range of phenomena...
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12/31/2014
Detailed Derivations of Small-Variance Asymptotics for some Hierarchical Bayesian Nonparametric Models
In this note we provide detailed derivations of two versions of small-va...
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02/24/2014
