Reconstruction of Excitatory Neuronal Connectivity via Metric Score Pooling and Regularization. - Chenyang Tao; Wei Lin 003; Jianfeng Feng (Neural Connectomics, 2014)

Canonical kernel dimension reduction. - Chenyang Tao; Jianfeng Feng (Comput. Stat. Data Anal., 2017)

Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications. - Chenyang Tao; Thomas E. Nichols; Xue Hua; Christopher R. K. Ching; Edmund T. Rolls; Paul M. Thompson; Jianfeng Feng (NeuroImage, 2017)

Adversarial Time-to-Event Modeling. - Paidamoyo Chapfuwa; Chenyang Tao; Chunyuan Li; Courtney Page; Benjamin Alan Goldstein; Lawrence Carin; Ricardo Henao (ICML, 2018)

Variational Inference and Model Selection with Generalized Evidence Bounds. - Liqun Chen 001; Chenyang Tao; Ruiyi Zhang 002; Ricardo Henao; Lawrence Carin (ICML, 2018)

Chi-square Generative Adversarial Network. - Chenyang Tao; Liqun Chen 001; Ricardo Henao; Jianfeng Feng; Lawrence Carin (ICML, 2018)

Adversarial Text Generation via Feature-Mover's Distance. - Liqun Chen 001; Shuyang Dai; Chenyang Tao; Haichao Zhang; Zhe Gan; Dinghan Shen; Yizhe Zhang 002; Guoyin Wang 002; Ruiyi Zhang 002; Lawrence Carin (NeurIPS, 2018)

Adversarial Text Generation via Feature-Mover's Distance. - Liqun Chen 001; Shuyang Dai; Chenyang Tao; Dinghan Shen; Zhe Gan; Haichao Zhang; Yizhe Zhang 002; Lawrence Carin (CoRR, 2018)

Improving Textual Network Embedding with Global Attention via Optimal Transport. - Liqun Chen 001; Guoyin Wang 002; Chenyang Tao; Dinghan Shen; Pengyu Cheng; Xinyuan Zhang 001; Wenlin Wang; Yizhe Zhang 002; Lawrence Carin (ACL (1), 2019)

Improving Sequence-to-Sequence Learning via Optimal Transport. - Liqun Chen 001; Yizhe Zhang 002; Ruiyi Zhang 002; Chenyang Tao; Zhe Gan; Haichao Zhang; Bai Li 001; Dinghan Shen; Changyou Chen; Lawrence Carin (ICLR (Poster), 2019)

Variational Annealing of GANs: A Langevin Perspective. - Chenyang Tao; Shuyang Dai; Liqun Chen 001; Ke Bai 001; Junya Chen; Chang Liu 030; Ruiyi Zhang 002; Georgiy V. Bobashev; Lawrence Carin (ICML, 2019)

On Fenchel Mini-Max Learning. - Chenyang Tao; Liqun Chen 001; Shuyang Dai; Junya Chen; Ke Bai 001; Dong Wang 037; Jianfeng Feng; Wenlian Lu; Georgiy V. Bobashev; Lawrence Carin (NeurIPS, 2019)

Improving Textual Network Learning with Variational Homophilic Embeddings. - Wenlin Wang; Chenyang Tao; Zhe Gan; Guoyin Wang 002; Liqun Chen 001; Xinyuan Zhang 001; Ruiyi Zhang 002; Qian Yang 003; Ricardo Henao; Lawrence Carin (NeurIPS, 2019)

Survival Function Matching for Calibrated Time-to-Event Predictions. - Paidamoyo Chapfuwa; Chenyang Tao; Lawrence Carin; Ricardo Henao (CoRR, 2019)

Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning. - Liqun Chen 001; Ke Bai 001; Chenyang Tao; Yizhe Zhang 002; Guoyin Wang 002; Wenlin Wang; Ricardo Henao; Lawrence Carin (AAAI, 2020)

Advancing weakly supervised cross-domain alignment with optimal transport. - Siyang Yuan; Ke Bai 001; Liqun Chen 001; Yizhe Zhang 002; Chenyang Tao; Chunyuan Li; Guoyin Wang 002; Ricardo Henao; Lawrence Carin (BMVC, 2020)

Variational learning of individual survival distributions. - Zidi Xiu; Chenyang Tao; Ricardo Henao (CHIL, 2020)

Improving Text Generation with Student-Forcing Optimal Transport. - Jianqiao Li; Chunyuan Li; Guoyin Wang 002; Hao Fu 002; Yuh-Chen Lin; Liqun Chen 001; Yizhe Zhang 002; Chenyang Tao; Ruiyi Zhang 002; Wenlin Wang; Dinghan Shen; Qian Yang 003; et al. (EMNLP (1), 2020)

Reconsidering Generative Objectives For Counterfactual Reasoning. - Danni Lu; Chenyang Tao; Junya Chen; Fan Li; Feng Guo; Lawrence Carin (NeurIPS, 2020)

Weakly supervised cross-domain alignment with optimal transport. - Siyang Yuan; Ke Bai 001; Liqun Chen 001; Yizhe Zhang 002; Chenyang Tao; Chunyuan Li; Guoyin Wang 002; Ricardo Henao; Lawrence Carin (CoRR, 2020)

Double Robust Representation Learning for Counterfactual Prediction. - Shuxi Zeng; Serge Assaad; Chenyang Tao; Shounak Datta; Lawrence Carin; Fan Li (CoRR, 2020)

Supercharging Imbalanced Data Learning With Causal Representation Transfer. - Junya Chen; Zidi Xiu; Benjamin Alan Goldstein; Ricardo Henao; Lawrence Carin; Chenyang Tao (CoRR, 2020)

Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models. - Dong Wang 037; Yuewei Yang; Chenyang Tao; Fanjie Kong; Ricardo Henao; Lawrence Carin (CoRR, 2020)

Variational Disentanglement for Rare Event Modeling. - Zidi Xiu; Chenyang Tao; Michael Gao; Connor Davis; Benjamin Alan Goldstein; Ricardo Henao (AAAI, 2021)

Counterfactual Representation Learning with Balancing Weights. - Serge Assaad; Shuxi Zeng; Chenyang Tao; Shounak Datta; Nikhil Mehta 002; Ricardo Henao; Fan Li; Lawrence Carin (AISTATS, 2021)

APo-VAE: Text Generation in Hyperbolic Space. - Shuyang Dai; Zhe Gan; Yu Cheng 001; Chenyang Tao; Lawrence Carin; Jingjing Liu 001 (NAACL-HLT, 2021)

Multi-Grained Knowledge Distillation for Named Entity Recognition. - Xuan Zhou; Xiao Zhang; Chenyang Tao; Junya Chen; Bing Xu; Wei Wang; Jing Xiao 006 (NAACL-HLT, 2021)

Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer. - Junya Chen; Zidi Xiu; Benjamin Goldstein 001; Ricardo Henao; Lawrence Carin; Chenyang Tao (NeurIPS, 2021)

Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization. - Qing Guo; Junya Chen; Dong Wang 037; Yuewei Yang; Xinwei Deng; Lawrence Carin; Fan Li; Chenyang Tao (CoRR, 2021)

Simpler, Faster, Stronger: Breaking The log-K Curse On Contrastive Learners With FlatNCE. - Junya Chen; Zhe Gan; Xuan Li; Qing Guo; Liqun Chen 001; Shuyang Gao; Tagyoung Chung; Yi Xu 011; Belinda Zeng; Wenlian Lu; Fan Li; Lawrence Carin; et al. (CoRR, 2021)

Imputation-Free Learning from Incomplete Observations. - Qitong Gao; Dong Wang 037; Joshua D. Amason; Siyang Yuan; Chenyang Tao; Ricardo Henao; Majda Hadziahmetovic; Lawrence Carin; Miroslav Pajic (CoRR, 2021)

Variational Inference with Holder Bounds. - Junya Chen; Danni Lu; Zidi Xiu; Ke Bai 001; Lawrence Carin; Chenyang Tao (CoRR, 2021)

Finite-Time Consensus Learning for Decentralized Optimization with Nonlinear Gossiping. - Junya Chen; Sijia Wang; Lawrence Carin; Chenyang Tao (CoRR, 2021)

Gradient Importance Learning for Incomplete Observations. - Qitong Gao; Dong Wang 037; Joshua David Amason; Siyang Yuan; Chenyang Tao; Ricardo Henao; Majda Hadziahmetovic; Lawrence Carin; Miroslav Pajic (ICLR, 2022)

Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization. - Qing Guo; Junya Chen; Dong Wang 037; Yuewei Yang; Xinwei Deng; Jing Huang; Lawrence Carin; Fan Li; Chenyang Tao (NeurIPS, 2022)

Weakly Supervised Data Augmentation Through Prompting for Dialogue Understanding. - Maximillian Chen; Alexandros Papangelis; Chenyang Tao; Andy Rosenbaum; Seokhwan Kim; Yang Liu 004; Zhou Yu 005; Dilek Hakkani-Tur (CoRR, 2022)

Unsupervised Melody-to-Lyrics Generation. - Yufei Tian; Anjali Narayan-Chen; Shereen Oraby; Alessandra Cervone; Gunnar A. Sigurdsson; Chenyang Tao; Wenbo Zhao 006; Tagyoung Chung; Jing Huang 020; Nanyun Peng 001 (ACL (1), 2023)

PLACES: Prompting Language Models for Social Conversation Synthesis. - Maximillian Chen; Alexandros Papangelis; Chenyang Tao; Seokhwan Kim; Andy Rosenbaum; Yang Liu 004; Zhou Yu 005; Dilek Hakkani-Tur (EACL (Findings), 2023)

Unsupervised Melody-Guided Lyrics Generation. - Yufei Tian; Anjali Narayan-Chen; Shereen Oraby; Alessandra Cervone; Gunnar A. Sigurdsson; Chenyang Tao; Wenbo Zhao 006; Tagyoung Chung; Jing Huang 020; Nanyun Peng 001 (CoRR, 2023)

Unsupervised Melody-to-Lyric Generation. - Yufei Tian; Anjali Narayan-Chen; Shereen Oraby; Alessandra Cervone; Gunnar A. Sigurdsson; Chenyang Tao; Wenbo Zhao 006; Tagyoung Chung; Jing Huang 020; Nanyun Peng 001 (CoRR, 2023)

On Compositionality and Improved Training of NADO. - Sidi Lu; Wenbo Zhao 006; Chenyang Tao; Arpit Gupta; Shanchan Wu; Tagyoung Chung; Nanyun Peng 001 (CoRR, 2023)

Calibration and Uncertainty in Neural Time-to-Event Modeling. - Paidamoyo Chapfuwa; Chenyang Tao; Chunyuan Li; Irfan Khan; Karen Chandross; Michael J. Pencina; Lawrence Carin; Ricardo Henao (IEEE Trans. Neural Networks Learn. Syst., 2023)

MARS: Meaning-Aware Response Scoring for Uncertainty Estimation in Generative LLMs. - Yavuz Faruk Bakman; Duygu Nur Yaldiz; Baturalp Buyukates; Chenyang Tao; Dimitrios Dimitriadis; Salman Avestimehr (ACL (1), 2024)

CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning. - Erum Mushtaq; Duygu Nur Yaldiz; Yavuz Faruk Bakman; Jie Ding 002; Chenyang Tao; Dimitrios Dimitriadis; Salman Avestimehr (ECCV (80), 2024)

DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models. - Sidi Lu; Wenbo Zhao 006; Chenyang Tao; Arpit Gupta; Shanchan Wu; Tagyoung Chung; Nanyun Peng 001 (ICML, 2024)

Predicting Uncertainty of Generative LLMs with MARS: Meaning-Aware Response Scoring. - Yavuz Faruk Bakman; Duygu Nur Yaldiz; Baturalp Buyukates; Salman Avestimehr; Chenyang Tao; Dimitrios Dimitriadis (ISIT, 2024)

Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs. - Duygu Nur Yaldiz; Yavuz Faruk Bakman; Baturalp Buyukates; Chenyang Tao; Anil Ramakrishna; Dimitrios Dimitriadis; Salman Avestimehr (CoRR, 2024)

Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs. - Duygu Nur Yaldiz; Yavuz Faruk Bakman; Baturalp Buyukates; Chenyang Tao; Anil Ramakrishna; Dimitrios Dimitriadis; Jieyu Zhao; Salman Avestimehr (NAACL (Findings), 2025)