Linh Tran | DeepAI

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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...

0 Md Ferdous Alam, et al. ∙

∙ 05/26/2023

Generalizable Pose Estimation Using Implicit Scene Representations

6-DoF pose estimation is an essential component of robotic manipulation ...

0 Vaibhav Saxena, et al. ∙

∙ 09/30/2022

MaskTune: Mitigating Spurious Correlations by Forcing to Explore

A fundamental challenge of over-parameterized deep learning models is le...

6 Saeid Asgari Taghanaki, et al. ∙

∙ 07/04/2022

Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness

Batch normalization (BN) is a ubiquitous technique for training deep neu...

4 Saeid Asgari Taghanaki, et al. ∙

∙ 02/04/2022

COIL: Constrained Optimization in Learned Latent Space – Learning Representations for Valid Solutions

Constrained optimization problems can be difficult because their search ...

27 Peter J Bentley, et al. ∙

∙ 10/23/2021

Group-disentangled Representation Learning with Weakly-Supervised Regularization

Learning interpretable and human-controllable representations that uncov...

5 Linh Tran, et al. ∙

∙ 02/03/2021

Noise-robust classification with hypergraph neural network

This paper presents a novel version of the hypergraph neural network met...

0 Nguyen Trinh Vu Dang, et al. ∙

∙ 01/06/2021

Cauchy-Schwarz Regularized Autoencoder

Recent work in unsupervised learning has focused on efficient inference ...

34 Linh Tran, et al. ∙

∙ 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...

0 Izhak Shafran, et al. ∙

∙ 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...

6 Jakub Świątkowski, et al. ∙

∙ 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...

27 Florian Wenzel, et al. ∙

∙ 01/14/2020

Hydra: Preserving Ensemble Diversity for Model Distillation

Ensembles of models have been empirically shown to improve predictive pe...

1 Linh Tran, et al. ∙

∙ 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., ...

0 Nan Du, et al. ∙

∙ 08/29/2019

Solve fraud detection problem by using graph based learning methods

The credit cards' fraud transactions detection is the important problem ...

12 Loc Tran, et al. ∙

∙ 06/05/2019

Extracting Symptoms and their Status from Clinical Conversations

This paper describes novel models tailored for a new application, that o...

0 Nan Du, et al. ∙

∙ 10/06/2018

Robust variance estimation and inference for causal effect estimation

We consider a longitudinal data structure consisting of baseline covaria...

0 Linh Tran, et al. ∙

∙ 12/03/2017

GAGAN: Geometry-Aware Generative Adverserial Networks

Deep generative models learned through adversarial training have become ...

0 Jean Kossaifi, et al. ∙

∙ 08/26/2013

The Generalized Mean Information Coefficient

Reshef & Reshef recently published a paper in which they present a metho...

0 Alexander Luedtke, et al. ∙

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