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09/05/2023
Representation Learning for Sequential Volumetric Design Tasks
Volumetric design, also called massing design, is the first and critical...
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05/26/2023
Generalizable Pose Estimation Using Implicit Scene Representations
6-DoF pose estimation is an essential component of robotic manipulation ...
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09/30/2022
MaskTune: Mitigating Spurious Correlations by Forcing to Explore
A fundamental challenge of over-parameterized deep learning models is le...
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07/04/2022
Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness
Batch normalization (BN) is a ubiquitous technique for training deep neu...
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02/04/2022
COIL: Constrained Optimization in Learned Latent Space – Learning Representations for Valid Solutions
Constrained optimization problems can be difficult because their search ...
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10/23/2021
Group-disentangled Representation Learning with Weakly-Supervised Regularization
Learning interpretable and human-controllable representations that uncov...
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02/03/2021
Noise-robust classification with hypergraph neural network
This paper presents a novel version of the hypergraph neural network met...
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01/06/2021
Cauchy-Schwarz Regularized Autoencoder
Recent work in unsupervised learning has focused on efficient inference ...
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03/12/2020
The Medical Scribe: Corpus Development and Model Performance Analyses
There is a growing interest in creating tools to assist in clinical note...
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02/07/2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks
Variational Bayesian Inference is a popular methodology for approximatin...
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02/06/2020
How Good is the Bayes Posterior in Deep Neural Networks Really?
During the past five years the Bayesian deep learning community has deve...
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01/14/2020
Hydra: Preserving Ensemble Diversity for Model Distillation
Ensembles of models have been empirically shown to improve predictive pe...
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08/30/2019
Learning to Infer Entities, Properties and their Relations from Clinical Conversations
Recently we proposed the Span Attribute Tagging (SAT) Model (Du et al., ...
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08/29/2019
Solve fraud detection problem by using graph based learning methods
The credit cards' fraud transactions detection is the important problem ...
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06/05/2019
Extracting Symptoms and their Status from Clinical Conversations
This paper describes novel models tailored for a new application, that o...
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10/06/2018
Robust variance estimation and inference for causal effect estimation
We consider a longitudinal data structure consisting of baseline covaria...
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12/03/2017
GAGAN: Geometry-Aware Generative Adverserial Networks
Deep generative models learned through adversarial training have become ...
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08/26/2013