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06/13/2023
Causal Mediation Analysis with Multi-dimensional and Indirectly Observed Mediators
Causal mediation analysis (CMA) is a powerful method to dissect the tota...
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02/03/2023
Domain Adaptation via Rebalanced Sub-domain Alignment
Unsupervised domain adaptation (UDA) is a technique used to transfer kno...
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01/26/2023
Estimating Causal Effects using a Multi-task Deep Ensemble
Over the past few decades, a number of methods have been proposed for ca...
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05/15/2022
Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel
It is challenging to guide neural network (NN) learning with prior knowl...
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05/13/2022
Multiple Domain Causal Networks
Observational studies are regarded as economic alternatives to randomize...
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01/07/2022
AugmentedPCA: A Python Package of Supervised and Adversarial Linear Factor Models
Deep autoencoders are often extended with a supervised or adversarial lo...
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10/04/2021
Estimating Potential Outcome Distributions with Collaborating Causal Networks
Many causal inference approaches have focused on identifying an individu...
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09/09/2021
Supervising the Decoder of Variational Autoencoders to Improve Scientific Utility
Probabilistic generative models are attractive for scientific modeling b...
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04/10/2020
Supervised Autoencoders Learn Robust Joint Factor Models of Neural Activity
Factor models are routinely used for dimensionality reduction in modelin...
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02/12/2020
Estimating Uncertainty Intervals from Collaborating Networks
Effective decision making requires understanding the uncertainty inheren...
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10/05/2019
Gaussian-Process-Based Dynamic Embedding for Textual Networks
Textual network embedding aims to learn low-dimensional representations ...
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06/04/2019
The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis
Despite the widespread usage of machine learning throughout organization...
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12/06/2018
StoryGAN: A Sequential Conditional GAN for Story Visualization
In this work we propose a new task called Story Visualization. Given a m...
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10/01/2017
Video Generation From Text
Generating videos from text has proven to be a significant challenge for...
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09/03/2016
Stochastic Bouncy Particle Sampler
We introduce a novel stochastic version of the non-reversible, rejection...
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03/07/2016
Partition Functions from Rao-Blackwellized Tempered Sampling
Partition functions of probability distributions are important quantitie...
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12/25/2015
Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization
Stochastic gradient Markov chain Monte Carlo (SG-MCMC) methods are Bayes...
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12/23/2015
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks
Effective training of deep neural networks suffers from two main issues....
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11/13/2015
Neuroprosthetic decoder training as imitation learning
Neuroprosthetic brain-computer interfaces function via an algorithm whic...
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09/23/2015
