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Chin-Wei Huang
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2020 – today
- 2024
- [j8]Chin-Wei Huang
:
Using the hybrid undesirable network data envelopment analysis model to evaluate the efficiency of Taiwan's social care system. RAIRO Oper. Res. 58(5): 4531-4551 (2024) - [c16]Chin-Wei Huang, Chien-Hui Su, Po-Chih Kuo:
Decoding Visual Perception from EEG Using Explainable Graph Neural Network. EMBC 2024: 1-4 - [i20]Chin-Wei Huang, Mu-Yi Shen, Kuan-Chang Shih, Shih-Chih Lin, Chi-Yu Chen, Po-Chih Kuo:
LTCXNet: Advancing Chest X-Ray Analysis with Solutions for Long-Tailed Multi-Label Classification and Fairness Challenges. CoRR abs/2411.10746 (2024) - 2023
- [c15]Chin-Wei Huang, Yi-Fei Chuang:
Taiwan's Experience with Emergency Distribution of Masks dring COVID-19 Pandemic. IIAI-AAI 2023: 594-599 - [i19]Marloes Arts, Victor Garcia Satorras, Chin-Wei Huang, Daniel Zügner, Marco Federici, Cecilia Clementi, Frank Noé, Robert Pinsler, Rianne van den Berg:
Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics. CoRR abs/2302.00600 (2023) - 2022
- [j7]Jenq-Haur Wang
, Chin-Wei Huang, Mehdi Norouzi:
Improving Rumor Detection by Image Captioning and Multi-Cell Bi-RNN With Self-Attention in Social Networks. Int. J. Data Warehous. Min. 18(1): 1-17 (2022) - [c14]Shawn Tan, Chin-Wei Huang, Alessandro Sordoni, Aaron C. Courville:
Learning to Dequantise with Truncated Flows. ICLR 2022 - [c13]Chin-Wei Huang, Milad Aghajohari, Joey Bose, Prakash Panangaden, Aaron C. Courville:
Riemannian Diffusion Models. NeurIPS 2022 - [i18]Chin-Wei Huang, Milad Aghajohari, Avishek Joey Bose, Prakash Panangaden, Aaron C. Courville:
Riemannian Diffusion Models. CoRR abs/2208.07949 (2022) - 2021
- [j6]Chin-Wei Huang:
Using a hybrid two-stage DEA model to analyze the profitability and marketability of medical manufacturing firms. Int. Trans. Oper. Res. 28(1): 470-492 (2021) - [c12]Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron C. Courville:
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization. ICLR 2021 - [c11]Chin-Wei Huang, Jae Hyun Lim, Aaron C. Courville:
A Variational Perspective on Diffusion-Based Generative Models and Score Matching. NeurIPS 2021: 22863-22876 - [i17]Chin-Wei Huang, Jae Hyun Lim, Aaron C. Courville:
A Variational Perspective on Diffusion-Based Generative Models and Score Matching. CoRR abs/2106.02808 (2021) - 2020
- [c10]Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville:
Stochastic Neural Network with Kronecker Flow. AISTATS 2020: 4184-4194 - [c9]Jae Hyun Lim, Aaron C. Courville, Christopher J. Pal, Chin-Wei Huang:
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation. ICML 2020: 6061-6071 - [i16]Chin-Wei Huang, Laurent Dinh, Aaron C. Courville:
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models. CoRR abs/2002.07101 (2020) - [i15]Jae Hyun Lim, Aaron C. Courville, Christopher J. Pal, Chin-Wei Huang:
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation. CoRR abs/2006.05164 (2020) - [i14]Brady Neal, Chin-Wei Huang, Sunand Raghupathi:
RealCause: Realistic Causal Inference Benchmarking. CoRR abs/2011.15007 (2020) - [i13]Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron C. Courville:
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization. CoRR abs/2012.05942 (2020)
2010 – 2019
- 2019
- [c8]Shih-Yu Chen
, Gwo Giun Chris Lee, Tai-Ping Wang, Chin-Wei Huang, Jia-Hong Chen, Chang-Ling Tsai:
Reconfigurable Edge via Analytics Architecture. AICAS 2019: 117-121 - [c7]Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron C. Courville:
Hierarchical Importance Weighted Autoencoders. ICML 2019: 2869-2878 - [c6]Fan-Yun Sun, Meng Qu, Jordan Hoffmann, Chin-Wei Huang, Jian Tang:
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning. NeurIPS 2019: 512-522 - [c5]Gwo Giun Chris Lee, Chin-Wei Huang, Jia-Hong Chen, Shih-Yu Chen
, Hsiu-Ling Chen:
AIFood: A Large Scale Food Images Dataset for Ingredient Recognition. TENCON 2019: 802-805 - [c4]Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron C. Courville:
Probability Distillation: A Caveat and Alternatives. UAI 2019: 1212-1221 - [i12]Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron C. Courville:
Hierarchical Importance Weighted Autoencoders. CoRR abs/1905.04866 (2019) - [i11]Chin-Wei Huang, Aaron C. Courville:
Note on the bias and variance of variational inference. CoRR abs/1906.03708 (2019) - [i10]Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville:
Stochastic Neural Network with Kronecker Flow. CoRR abs/1906.04282 (2019) - [i9]Fan-Yun Sun, Meng Qu, Jordan Hoffmann, Chin-Wei Huang, Jian Tang:
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning. CoRR abs/1906.07159 (2019) - [i8]Shawn Tan, Yikang Shen, Chin-Wei Huang, Aaron C. Courville:
Investigating Biases in Textual Entailment Datasets. CoRR abs/1906.09635 (2019) - 2018
- [c3]Yikang Shen, Zhouhan Lin, Chin-Wei Huang, Aaron C. Courville:
Neural Language Modeling by Jointly Learning Syntax and Lexicon. ICLR (Poster) 2018 - [c2]Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron C. Courville:
Neural Autoregressive Flows. ICML 2018: 2083-2092 - [c1]Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville:
Improving Explorability in Variational Inference with Annealed Variational Objectives. NeurIPS 2018: 9724-9734 - [i7]Yikang Shen, Shawn Tan, Chin-Wei Huang, Aaron C. Courville:
Generating Contradictory, Neutral, and Entailing Sentences. CoRR abs/1803.02710 (2018) - [i6]Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron C. Courville:
Neural Autoregressive Flows. CoRR abs/1804.00779 (2018) - [i5]Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville:
Improving Explorability in Variational Inference with Annealed Variational Objectives. CoRR abs/1809.01818 (2018) - 2017
- [i4]Chin-Wei Huang, Ahmed Touati, Laurent Dinh, Michal Drozdzal, Mohammad Havaei, Laurent Charlin, Aaron C. Courville:
Learnable Explicit Density for Continuous Latent Space and Variational Inference. CoRR abs/1710.02248 (2017) - [i3]David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron C. Courville:
Bayesian Hypernetworks. CoRR abs/1710.04759 (2017) - [i2]Yikang Shen, Zhouhan Lin, Chin-Wei Huang, Aaron C. Courville:
Neural Language Modeling by Jointly Learning Syntax and Lexicon. CoRR abs/1711.02013 (2017) - [i1]Chin-Wei Huang
, Luc Baron, Marek Balazinski, Sofiane Achiche
:
Comprehensive model optimization in pulp quality prediction: a machine learning approach. PeerJ Prepr. 5: e2749 (2017) - 2016
- [j5]Chin-Wei Huang, Yung-Ho Chiu, Chien-heng Tu, Zheng-ying Luo, Zebin Wang:
Using the nonhomogeneous frontier two-stage DEA model to assess the efficiencies of expense utilization and operation of the Taiwanese hotel industry. Int. Trans. Oper. Res. 23(6): 1067-1087 (2016) - 2012
- [j4]Yung-Ho Chiu, Chin-Wei Huang, Chung-Te Ting:
A non-radial measure of different systems for Taiwanese tourist hotels' efficiency assessment. Central Eur. J. Oper. Res. 20(1): 45-63 (2012) - 2011
- [j3]Yung-Ho Chiu, Chin-Wei Huang, Chung-Te Ting:
Measuring the Repair Performance for stricken Cultivated Land and Agricultural Efficiency in China with a Modified Two-Stage DEA Model. Asia Pac. J. Oper. Res. 28(5): 633-649 (2011) - [j2]Yung-Ho Chiu, Chin-Wei Huang, Chun-Mei Ma:
Assessment of China transit and economic efficiencies in a modified value-chains DEA model. Eur. J. Oper. Res. 209(2): 95-103 (2011)
2000 – 2009
- 2009
- [j1]Jian-Da Wu, Mingsian R. Bai
, Fu-Cheng Su, Chin-Wei Huang:
An expert system for the diagnosis of faults in rotating machinery using adaptive order-tracking algorithm. Expert Syst. Appl. 36(3): 5424-5431 (2009)
Coauthor Index

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