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06/20/2023
Copula-Based Deep Survival Models for Dependent Censoring
A survival dataset describes a set of instances (e.g. patients) and prov...
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02/09/2023
Modeling and Forecasting COVID-19 Cases using Latent Subpopulations
Classical epidemiological models assume homogeneous populations. There h...
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01/14/2022
Domain-shift adaptation via linear transformations
A predictor, f_A : X → Y, learned with data from a source domain (A) mig...
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11/11/2021
Variational Auto-Encoder Architectures that Excel at Causal Inference
Estimating causal effects from observational data (at either an individu...
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06/03/2021
SIMLR: Machine Learning inside the SIR model for COVID-19 Forecasting
Accurate forecasts of the number of newly infected people during an epid...
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02/11/2021
Sample Efficient Learning of Image-Based Diagnostic Classifiers Using Probabilistic Labels
Deep learning approaches often require huge datasets to achieve good gen...
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10/24/2020
Shared Space Transfer Learning for analyzing multi-site fMRI data
Multi-voxel pattern analysis (MVPA) learns predictive models from task-b...
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12/19/2019
Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation
Counterfactual reasoning is an important paradigm applicable in many fie...
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09/11/2019
Domain Aggregation Networks for Multi-Source Domain Adaptation
In many real-world applications, we want to exploit multiple source data...
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06/25/2019
Simultaneous Prediction Intervals for Patient-Specific Survival Curves
Accurate models of patient survival probabilities provide important info...
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03/29/2019
The Challenge of Predicting Meal-to-meal Blood Glucose Concentrations for Patients with Type I Diabetes
Patients with Type I Diabetes (T1D) must take insulin injections to prev...
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03/25/2019
Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach
Cancer is one of the leading cause of death, worldwide. Many believe tha...
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11/28/2018
Effective Ways to Build and Evaluate Individual Survival Distributions
An accurate model of a patient's individual survival distribution can he...
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12/01/2017
Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks
Smart systems that can accurately diagnose patients with mental disorder...
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01/01/2016
Stochastic Neural Networks with Monotonic Activation Functions
We propose a Laplace approximation that creates a stochastic unit from a...
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09/28/2015
Boolean Matrix Factorization and Noisy Completion via Message Passing
Boolean matrix factorization and Boolean matrix completion from noisy ob...
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09/25/2014
Revisiting Algebra and Complexity of Inference in Graphical Models
This paper studies the form and complexity of inference in graphical mod...
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09/04/2014
Accurate, fully-automated NMR spectral profiling for metabolomics
Many diseases cause significant changes to the concentrations of small m...
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06/04/2014
Augmentative Message Passing for Traveling Salesman Problem and Graph Partitioning
The cutting plane method is an augmentative constrained optimization pro...
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05/06/2014
Training Restricted Boltzmann Machine by Perturbation
A new approach to maximum likelihood learning of discrete graphical mode...
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01/26/2014
Perturbed Message Passing for Constraint Satisfaction Problems
We introduce an efficient message passing scheme for solving Constraint ...
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02/06/2013
Learning Bayesian Nets that Perform Well
A Bayesian net (BN) is more than a succinct way to encode a probabilisti...
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01/23/2013
Comparing Bayesian Network Classifiers
In this paper, we empirically evaluate algorithms for learning four type...
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01/10/2013
Bayesian Error-Bars for Belief Net Inference
A Bayesian Belief Network (BN) is a model of a joint distribution over a...
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10/19/2012
Budgeted Learning of Naive-Bayes Classifiers
Frequently, acquiring training data has an associated cost. We consider ...
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07/11/2012
Active Model Selection
Classical learning assumes the learner is given a labeled data sample, f...
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06/18/2012
A Generalized Loop Correction Method for Approximate Inference in Graphical Models
Belief Propagation (BP) is one of the most popular methods for inference...
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06/13/2012
Speeding Up Planning in Markov Decision Processes via Automatically Constructed Abstractions
In this paper, we consider planning in stochastic shortest path (SSP) pr...
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05/09/2012
