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09/28/2021
All-Around Real Label Supervision: Cyclic Prototype Consistency Learning for Semi-supervised Medical Image Segmentation
Semi-supervised learning has substantially advanced medical image segmen...
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09/24/2021
Optimization-based Causal Estimation from Heterogenous Environments
This paper presents a new optimization approach to causal estimation. Gi...
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09/08/2021
Desiderata for Representation Learning: A Causal Perspective
Representation learning constructs low-dimensional representations to su...
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08/19/2021
Learning Equilibria in Matching Markets from Bandit Feedback
Large-scale, two-sided matching platforms must find market outcomes that...
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06/21/2021
Confidence-Guided Radiology Report Generation
Medical imaging plays a pivotal role in diagnosis and treatment in clini...
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06/03/2021
Noisy Labels are Treasure: Mean-Teacher-Assisted Confident Learning for Hepatic Vessel Segmentation
Manually segmenting the hepatic vessels from Computer Tomography (CT) is...
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03/30/2021
Multi-Source Causal Inference Using Control Variates
While many areas of machine learning have benefited from the increasing ...
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10/19/2020
Double-Uncertainty Weighted Method for Semi-supervised Learning
Though deep learning has achieved advanced performance recently, it rema...
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10/19/2020
Modality-Pairing Learning for Brain Tumor Segmentation
Automatic brain tumor segmentation from multi-modality Magnetic Resonanc...
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10/10/2020
Point process models for sequence detection in high-dimensional neural spike trains
Sparse sequences of neural spikes are posited to underlie aspects of wor...
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06/23/2020
Does Non-COVID19 Lung Lesion Help? Investigating Transferability in COVID-19 CT Image Segmentation
Coronavirus disease 2019 (COVID-19) is a highly contagious virus spreadi...
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05/14/2020
Thermodynamically Stable DNA Code Design using a Similarity Significance Model
DNA code design aims to generate a set of DNA sequences (codewords) with...
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04/27/2020
Towards Efficient COVID-19 CT Annotation: A Benchmark for Lung and Infection Segmentation
Accurate segmentation of lung and infection in COVID-19 CT scans plays a...
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03/10/2020
Towards Clarifying the Theory of the Deconfounder
Wang and Blei (2019) studies multiple causal inference and proposes the ...
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03/01/2020
Harmonics Based Representation in Clarinet Tone Quality Evaluation
Music tone quality evaluation is generally performed by experts. It coul...
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12/02/2019
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 Challenge
There is a large body of literature linking anatomic and geometric chara...
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10/15/2019
The Blessings of Multiple Causes: A Reply to Ogburn et al. (2019)
Ogburn et al. (2019, arXiv:1910.05438) discuss "The Blessings of Multipl...
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10/05/2019
Cascaded Volumetric Convolutional Network for Kidney Tumor Segmentation from CT volumes
Automated segmentation of kidney and tumor from 3D CT scans is necessary...
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08/24/2019
Augmented Unlocking Techniques for Smartphones Using Pre-Touch Information
Smartphones store a significant amount of personal and private informati...
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06/10/2019
Multimodal Data Fusion of Non-Gaussian Spatial Fields in Sensor Networks
We develop a robust data fusion algorithm for field reconstruction of mu...
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05/30/2019
Multiple Causes: A Causal Graphical View
Unobserved confounding is a major hurdle for causal inference from obser...
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05/26/2019
Large Sample Properties of Matching for Balance
Matching methods are widely used for causal inference in observational s...
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05/26/2019
Equal Opportunity and Affirmative Action via Counterfactual Predictions
Machine learning (ML) can automate decision-making by learning to predic...
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05/26/2019
Variational Bayes under Model Misspecification
Variational Bayes (VB) is a scalable alternative to Markov chain Monte C...
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04/03/2019
The Medical Deconfounder: Assessing Treatment Effect with Electronic Health Records (EHRs)
Causal estimation of treatment effect has an important role in guiding p...
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02/11/2019
Using Embeddings to Correct for Unobserved Confounding
We consider causal inference in the presence of unobserved confounding. ...
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08/20/2018
The Deconfounded Recommender: A Causal Inference Approach to Recommendation
The goal of a recommender system is to show its users items that they wi...
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06/08/2018
Black Box FDR
Analyzing large-scale, multi-experiment studies requires scientists to t...
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05/17/2018
The Blessings of Multiple Causes
Causal inference from observation data often assumes "strong ignorabilit...
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11/27/2017
Robust variable screening for regression using factor profiling
Sure Independence Screening is a fast procedure for variable selection i...
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05/09/2017
Frequentist Consistency of Variational Bayes
A key challenge for modern Bayesian statistics is how to perform scalabl...
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06/13/2016
