Search Results for author: Linh Tran

Found 22 papers, 6 papers with code

Representation Learning for Sequential Volumetric Design Tasks

no code implementations5 Sep 2023 Md Ferdous Alam, Yi Wang, Linh Tran, Chin-Yi Cheng, Jieliang Luo

We develop the preference model by estimating the density of the learned representations whereas we train an autoregressive transformer model for sequential design generation.

Representation Learning

Generalizable Pose Estimation Using Implicit Scene Representations

no code implementations26 May 2023 Vaibhav Saxena, Kamal Rahimi Malekshan, Linh Tran, Yotto Koga

Most widely used methods learn to infer the object pose in a discriminative setup where the model filters useful information to infer the exact pose of the object.

Density Estimation Object +1

MaskTune: Mitigating Spurious Correlations by Forcing to Explore

1 code implementation30 Sep 2022 Saeid Asgari Taghanaki, Aliasghar Khani, Fereshte Khani, Ali Gholami, Linh Tran, Ali Mahdavi-Amiri, Ghassan Hamarneh

A fundamental challenge of over-parameterized deep learning models is learning meaningful data representations that yield good performance on a downstream task without over-fitting spurious input features.

Counterbalancing Teacher: Regularizing Batch Normalized Models for Robustness

no code implementations4 Jul 2022 Saeid Asgari Taghanaki, Ali Gholami, Fereshte Khani, Kristy Choi, Linh Tran, Ran Zhang, Aliasghar Khani

Batch normalization (BN) is a ubiquitous technique for training deep neural networks that accelerates their convergence to reach higher accuracy.

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

1 code implementation4 Feb 2022 Peter J Bentley, Soo Ling Lim, Adam Gaier, Linh Tran

Constrained optimization problems can be difficult because their search spaces have properties not conducive to search, e. g., multimodality, discontinuities, or deception.

Evolutionary Algorithms valid

Group-disentangled Representation Learning with Weakly-Supervised Regularization

no code implementations23 Oct 2021 Linh Tran, Amir Hosein Khasahmadi, Aditya Sanghi, Saeid Asgari

Learning interpretable and human-controllable representations that uncover factors of variation in data remains an ongoing key challenge in representation learning.

Disentanglement Transfer Learning

Cauchy-Schwarz Regularized Autoencoder

no code implementations6 Jan 2021 Linh Tran, Maja Pantic, Marc Peter Deisenroth

To perform efficient inference for GMM priors, we introduce a new constrained objective based on the Cauchy-Schwarz divergence, which can be computed analytically for GMMs.

Clustering Density Estimation

How Good is the Bayes Posterior in Deep Neural Networks Really?

1 code implementation ICML 2020 Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Świątkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin

In this work we cast doubt on the current understanding of Bayes posteriors in popular deep neural networks: we demonstrate through careful MCMC sampling that the posterior predictive induced by the Bayes posterior yields systematically worse predictions compared to simpler methods including point estimates obtained from SGD.

Bayesian Inference Uncertainty Quantification

To Detect Irregular Trade Behaviors In Stock Market By Using Graph Based Ranking Methods

no code implementations4 Sep 2019 Loc Tran, Linh Tran

To detect the irregular trade behaviors in the stock market is the important problem in machine learning field.

BIG-bench Machine Learning

Learning to Infer Entities, Properties and their Relations from Clinical Conversations

no code implementations IJCNLP 2019 Nan Du, Mingqiu Wang, Linh Tran, Gang Li, Izhak Shafran

Recently we proposed the Span Attribute Tagging (SAT) Model (Du et al., 2019) to infer clinical entities (e. g., symptoms) and their properties (e. g., duration).

Attribute Relation Extraction

Solve fraud detection problem by using graph based learning methods

no code implementations29 Aug 2019 Loc Tran, Tuan Tran, Linh Tran, An Mai

In this paper, we employ the graph p-Laplacian based semi-supervised learning methods combined with the undersampling techniques such as Cluster Centroids to solve the credit cards' fraud transactions detection problem.

Fraud Detection

Extracting Symptoms and their Status from Clinical Conversations

no code implementations ACL 2019 Nan Du, Kai Chen, Anjuli Kannan, Linh Tran, Yu-Hui Chen, Izhak Shafran

This paper describes novel models tailored for a new application, that of extracting the symptoms mentioned in clinical conversations along with their status.

Attribute

GAGAN: Geometry-Aware Generative Adversarial Networks

no code implementations CVPR 2018 Jean Kossaifi, Linh Tran, Yannis Panagakis, Maja Pantic

Deep generative models learned through adversarial training have become increasingly popular for their ability to generate naturalistic image textures.

Face Generation

The Generalized Mean Information Coefficient

no code implementations26 Aug 2013 Alexander Luedtke, Linh Tran

Here we present the Generalized Mean Information Coefficient (GMIC), a generalization of MIC which incorporates a tuning parameter that can be used to modify the complexity of the association favored by the measure.

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