Texture Segmentation by Minimizing Vector-Valued Energy Functionals: The Coupled-Membrane Model. - Tai Sing Lee; David Mumford; Alan L. Yuille (ECCV, 1992)

Representational Strategy in the Visual Cortex. - Tai Sing Lee (ICIP (2), 1994)

Region Competition: Unifying Snakes, Region Growing, Energy/Bayes/MDL for Multi-band Image Segmentation. - Song Chun Zhu; Tai Sing Lee; Alan L. Yuille (ICCV, 1995)

Image Representation Using 2D Gabor Wavelets. - Tai Sing Lee (IEEE Trans. Pattern Anal. Mach. Intell., 1996)

An Information-Theoretic Framework for Understanding Saccadic Eye Movements. - Tai Sing Lee; Stella X. Yu (NIPS, 1999)

A Bayesian decision approach to evaluate local and contextual information in spike trains. - Elise Cassidente; Xiaogang Yan; Tai Sing Lee (Neurocomputing, 2000)

What do V1 neurons tell us about saccadic suppression? - Stella X. Yu; Tai Sing Lee (Neurocomputing, 2000)

A Hierarchical Markov Random Field Model for Figure-Ground Segregation. - Stella X. Yu; Tai Sing Lee; Takeo Kanade (EMMCVPR, 2001)

A unified model of spatial and object attention based on inter-cortical biased competition. - Gustavo Deco; Tai Sing Lee (Neurocomputing, 2002)

Spike train analysis for single trial data. - Richard Romero; Tai Sing Lee (Neurocomputing, 2002)

Decoding V1 Neuronal Activity using Particle Filtering with Volterra Kernels. - Ryan C. Kelly; Tai Sing Lee (NIPS, 2003)

Adaptation of the temporal receptive fields of macaque V1 neurons. - Richard Romero; Yuguo Yu; Pedram Afshar; Tai Sing Lee (Neurocomputing, 2003)

Adaptation of the transfer function of the Hodgkin-Huxley (HH) neuronal model. - Yuguo Yu; Tai Sing Lee (Neurocomputing, 2003)

Decoding visual input from V1 neuronal activity with particle filtering. - Ryan C. Kelly; Tai Sing Lee (Neurocomputing, 2004)

Scaling Laws in Natural Scenes and the Inference of 3D Shape. - Brian Potetz; Tai Sing Lee (NIPS, 2005)

Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video. - Thomas S. Stepleton; Tai Sing Lee (WACV/MOTION, 2005)

Adaptive contrast gain control and information maximization. - Yuguo Yu; Tai Sing Lee (Neurocomputing, 2005)

Neurophysiological Evidence of Cooperative Mechanisms for Stereo Computation. - Jason M. Samonds; Brian Potetz; Tai Sing Lee (NIPS, 2006)

Efficient belief propagation for higher-order cliques using linear constraint nodes. - Brian Potetz; Tai Sing Lee (Comput. Vis. Image Underst., 2008)

The Block Diagonal Infinite Hidden Markov Model. - Thomas S. Stepleton; Zoubin Ghahramani; Geoffrey J. Gordon; Tai Sing Lee (AISTATS, 2009)

Accounting for network effects in neuronal responses using L1 regularized point process models. - Ryan C. Kelly; Matthew A. Smith 001; Robert E. Kass; Tai Sing Lee (NIPS, 2010)

Local field potentials indicate network state and account for neuronal response variability. - Ryan C. Kelly; Matthew A. Smith 001; Robert E. Kass; Tai Sing Lee (J. Comput. Neurosci., 2010)

Hybrid generative-discriminative classification using posterior divergence. - Xiong Li 004; Tai Sing Lee; Yuncai Liu (CVPR, 2011)

Stochastic Feature Mapping for PAC-Bayes Classification - Xiong Li 004; Tai Sing Lee; Yuncai Liu (CoRR, 2012)

Learning Discriminative Sufficient Statistics Score Space for Classification. - Xiong Li 004; Bin Wang 052; Yuncai Liu; Tai Sing Lee (ECML/PKDD (3), 2013)

Sample Skewness as a Statistical Measurement of Neuronal Tuning Sharpness. - Jason M. Samonds; Brian Potetz; Tai Sing Lee (Neural Comput., 2014)

Predictive Encoding of Contextual Relationships for Perceptual Inference, Interpolation and Prediction. - Mingmin Zhao; Chengxu Zhuang; Yizhou Wang 001; Tai Sing Lee (ICLR (Workshop), 2015)

Stochastic feature mapping for PAC-Bayes classification. - Xiong Li 004; Bin Wang 052; Yuncai Liu; Tai Sing Lee (Mach. Learn., 2015)

Learning Robust Object Recognition Using Composed Scenes from Generative Models. - Hao Wang; Xingyu Lin; Yimeng Zhang; Tai Sing Lee (CRV, 2017)

Learning to Associate Words and Images Using a Large-Scale Graph. - Heqing Ya; Haonan Sun; Jeffrey Helt; Tai Sing Lee (CRV, 2017)

Transfer of View-manifold Learning to Similarity Perception of Novel Objects. - Xingyu Lin; Hao Wang; Zhihao Li; Yimeng Zhang; Alan L. Yuille; Tai Sing Lee (ICLR (Poster), 2017)

A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits. - Wenhao Zhang 002; Si Wu 001; Brent Doiron; Tai Sing Lee (NeurIPS, 2019)

Recurrent Feedback Improves Feedforward Representations in Deep Neural Networks. - Siming Yan; Xuyang Fang; Bowen Xiao; Harold Rockwell; Yimeng Zhang; Tai Sing Lee (CoRR, 2019)

Convolutional neural network models of V1 responses to complex patterns. - Yimeng Zhang; Tai Sing Lee; Ming Li; Fang Liu; Shiming Tang (J. Comput. Neurosci., 2019)

SurfGen: Adversarial 3D Shape Synthesis with Explicit Surface Discriminators. - Andrew Luo; Tianqin Li; Wen-Hao Zhang; Tai Sing Lee (ICCV, 2021)

Recurrent networks improve neural response prediction and provide insights into underlying cortical circuits. - Yimeng Zhang; Harold Rockwell; Sicheng Dai; Ge Huang; Stephen Tsou; Yuanyuan Wei 001; Tai Sing Lee (CoRR, 2021)

Complexity and diversity in sparse code priors improve receptive field characterization of Macaque V1 neurons. - Ziniu Wu; Harold Rockwell; Yimeng Zhang; Shiming Tang; Tai Sing Lee (PLoS Comput. Biol., 2021)

Prototype memory and attention mechanisms for few shot image generation. - Tianqin Li; Zijie Li; Andrew Luo; Harold Rockwell; Amir Barati Farimani; Tai Sing Lee (ICLR, 2022)

Relating Human Perception of Musicality to Prediction in a Predictive Coding Model. - Nikolas McNeal; Jennifer Huang; Aniekan Umoren; Shuqi Dai; Roger B. Dannenberg; Richard Randall; Tai Sing Lee (CoRR, 2022)

Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity. - Tianqin Li; Ziqi Wen; Yangfan Li; Tai Sing Lee (NeurIPS, 2023)

A large calcium-imaging dataset reveals a systematic V4 organization for natural scenes. - Tianye Wang; Haoxuan Yao; Tai Sing Lee; Jiayi Hong; Yang Li; Hongfei Jiang; Ian Max Andolina; Shiming Tang (CoRR, 2023)

Does resistance to Style-Transfer equal Shape Bias? Evaluating Shape Bias by Distorted Shape. - Ziqi Wen; Tianqin Li; Tai Sing Lee (CoRR, 2023)

Incremental Learning and Self-Attention Mechanisms Improve Neural System Identification. - Isaac Lin; Tianye Wang; Shang Gao; Shiming Tang; Tai Sing Lee (CoRR, 2024)

Perceptual Inductive Bias Is What You Need Before Contrastive Learning. - Junru Zhao; Tianqin Li; Dunhan Jiang; Shenghao Wu; Alan Ramirez; Tai Sing Lee (CVPR, 2025)

Self-Attention-Based Contextual Modulation Improves Neural System Identification. - Isaac Lin; Tianye Wang; Shang Gao; Shiming Tang; Tai Sing Lee (ICLR, 2025)

From Local Cues to Global Percepts: Emergent Gestalt Organization in Self-Supervised Vision Models. - Tianqin Li; Ziqi Wen; Leiran Song; Jun Liu; Zhi Jing 003; Tai Sing Lee (CoRR, 2025)

Modeling Rapid Contextual Learning in the Visual Cortex with Fast-Weight Deep Autoencoder Networks. - Yue Li; Weifan Wang 009; Tai Sing Lee (CoRR, 2025)

Learning More by Seeing Less: Line Drawing Pretraining for Efficient, Transferable, and Human-Aligned Vision. - Tianqin Li; George Liu; Tai Sing Lee (CoRR, 2025)