An expert system for the diagnosis of faults in rotating machinery using adaptive order-tracking algorithm. - Jian-Da Wu; Mingsian R. Bai; Fu-Cheng Su; Chin-Wei Huang (Expert Syst. Appl., 2009)

Measuring the Repair Performance for stricken Cultivated Land and Agricultural Efficiency in China with a Modified Two-Stage DEA Model. - Yung-Ho Chiu; Chin-Wei Huang; Chung-Te Ting (Asia Pac. J. Oper. Res., 2011)

Assessment of China transit and economic efficiencies in a modified value-chains DEA model. - Yung-Ho Chiu; Chin-Wei Huang; Chun-Mei Ma (Eur. J. Oper. Res., 2011)

A non-radial measure of different systems for Taiwanese tourist hotels' efficiency assessment. - Yung-Ho Chiu; Chin-Wei Huang; Chung-Te Ting (Central Eur. J. Oper. Res., 2012)

Using the nonhomogeneous frontier two-stage DEA model to assess the efficiencies of expense utilization and operation of the Taiwanese hotel industry. - Chin-Wei Huang; Yung-Ho Chiu; Chien-heng Tu; Zheng-ying Luo; Zebin Wang (Int. Trans. Oper. Res., 2016)

Learnable Explicit Density for Continuous Latent Space and Variational Inference. - Chin-Wei Huang; Ahmed Touati; Laurent Dinh; Michal Drozdzal; Mohammad Havaei; Laurent Charlin; Aaron C. Courville (CoRR, 2017)

Bayesian Hypernetworks. - David Krueger 001; Chin-Wei Huang; Riashat Islam; Ryan Turner; Alexandre Lacoste; Aaron C. Courville (CoRR, 2017)

Comprehensive model optimization in pulp quality prediction: a machine learning approach. - Chin-Wei Huang; Luc Baron; Marek Balazinski; Sofiane Achiche (PeerJ Prepr., 2017)

Neural Language Modeling by Jointly Learning Syntax and Lexicon. - Yikang Shen; Zhouhan Lin; Chin-Wei Huang; Aaron C. Courville (ICLR (Poster), 2018)

Neural Autoregressive Flows. - Chin-Wei Huang; David Krueger 001; Alexandre Lacoste; Aaron C. Courville (ICML, 2018)

Improving Explorability in Variational Inference with Annealed Variational Objectives. - Chin-Wei Huang; Shawn Tan; Alexandre Lacoste; Aaron C. Courville (NeurIPS, 2018)

Generating Contradictory, Neutral, and Entailing Sentences. - Yikang Shen; Shawn Tan; Chin-Wei Huang; Aaron C. Courville (CoRR, 2018)

Reconfigurable Edge via Analytics Architecture. - Shih-Yu Chen; Gwo Giun Chris Lee; Tai-Ping Wang; Chin-Wei Huang; Jia-Hong Chen; Chang-Ling Tsai (AICAS, 2019)

Hierarchical Importance Weighted Autoencoders. - Chin-Wei Huang; Kris Sankaran; Eeshan Dhekane; Alexandre Lacoste; Aaron C. Courville (ICML, 2019)

vGraph: A Generative Model for Joint Community Detection and Node Representation Learning. - Fan-Yun Sun; Meng Qu; Jordan Hoffmann; Chin-Wei Huang; Jian Tang 005 (NeurIPS, 2019)

AIFood: A Large Scale Food Images Dataset for Ingredient Recognition. - Gwo Giun Chris Lee; Chin-Wei Huang; Jia-Hong Chen; Shih-Yu Chen; Hsiu-Ling Chen (TENCON, 2019)

Probability Distillation: A Caveat and Alternatives. - Chin-Wei Huang; Faruk Ahmed; Kundan Kumar; Alexandre Lacoste; Aaron C. Courville (UAI, 2019)

Note on the bias and variance of variational inference. - Chin-Wei Huang; Aaron C. Courville (CoRR, 2019)

Investigating Biases in Textual Entailment Datasets. - Shawn Tan; Yikang Shen; Chin-Wei Huang; Aaron C. Courville (CoRR, 2019)

Stochastic Neural Network with Kronecker Flow. - Chin-Wei Huang; Ahmed Touati; Pascal Vincent; Gintare Karolina Dziugaite; Alexandre Lacoste; Aaron C. Courville (AISTATS, 2020)

AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation. - Jae Hyun Lim 001; Aaron C. Courville; Christopher J. Pal; Chin-Wei Huang (ICML, 2020)

Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models. - Chin-Wei Huang; Laurent Dinh; Aaron C. Courville (CoRR, 2020)

RealCause: Realistic Causal Inference Benchmarking. - Brady Neal; Chin-Wei Huang; Sunand Raghupathi (CoRR, 2020)

Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization. - Chin-Wei Huang; Ricky T. Q. Chen; Christos Tsirigotis; Aaron C. Courville (ICLR, 2021)

A Variational Perspective on Diffusion-Based Generative Models and Score Matching. - Chin-Wei Huang; Jae Hyun Lim 001; Aaron C. Courville (NeurIPS, 2021)

Using a hybrid two-stage DEA model to analyze the profitability and marketability of medical manufacturing firms. - Chin-Wei Huang (Int. Trans. Oper. Res., 2021)

Learning to Dequantise with Truncated Flows. - Shawn Tan; Chin-Wei Huang; Alessandro Sordoni; Aaron C. Courville (ICLR, 2022)

Riemannian Diffusion Models. - Chin-Wei Huang; Milad Aghajohari; Joey Bose; Prakash Panangaden; Aaron C. Courville (NeurIPS, 2022)

Improving Rumor Detection by Image Captioning and Multi-Cell Bi-RNN With Self-Attention in Social Networks. - Jenq-Haur Wang; Chin-Wei Huang; Mehdi Norouzi (Int. J. Data Warehous. Min., 2022)

Taiwan's Experience with Emergency Distribution of Masks dring COVID-19 Pandemic. - Chin-Wei Huang; Yi-Fei Chuang (IIAI-AAI, 2023)

Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics. - Marloes Arts; Victor Garcia Satorras; Chin-Wei Huang; Daniel Zügner; Marco Federici; Cecilia Clementi; Frank Noé; Robert Pinsler; Rianne van den Berg (CoRR, 2023)

Decoding Visual Perception from EEG Using Explainable Graph Neural Network. - Chin-Wei Huang; Chien-Hui Su; Po-Chih Kuo (EMBC, 2024)

LTCXNet: Advancing Chest X-Ray Analysis with Solutions for Long-Tailed Multi-Label Classification and Fairness Challenges. - Chin-Wei Huang; Mu-Yi Shen; Kuan-Chang Shih; Shih-Chih Lin; Chi-Yu Chen; Po-Chih Kuo (CoRR, 2024)

Using the hybrid undesirable network data envelopment analysis model to evaluate the efficiency of Taiwan's social care system. - Chin-Wei Huang (RAIRO Oper. Res., 2024)

A generative model for inorganic materials design. - Claudio Zeni; Robert Pinsler; Daniel Zügner; Andrew Fowler; Matthew Horton; Xiang Fu 005; Zilong Wang; Aliaksandra Shysheya; Jonathan Crabbé; Shoko Ueda; Roberto Sordillo; Lixin Sun; et al. (Nat., 2025)

Accurate and scalable exchange-correlation with deep learning. - Giulia Luise; Chin-Wei Huang; Thijs Vogels; Derk P. Kooi; Sebastian Ehlert; Stephanie Lanius; Klaas J. H. Giesbertz; Amir Karton; Deniz Gunceler; Megan Stanley; Wessel P. Bruinsma; Lin Huang; et al. (CoRR, 2025)