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Tai Sing Lee
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2020 – today
- 2024
- [i12]Isaac Lin, Tianye Wang, Shang Gao, Shiming Tang, Tai Sing Lee:
Incremental Learning and Self-Attention Mechanisms Improve Neural System Identification. CoRR abs/2406.07843 (2024) - 2023
- [c21]Tianqin Li, Ziqi Wen, Yangfan Li, Tai Sing Lee:
Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity. NeurIPS 2023 - [i11]Tianye Wang
, Haoxuan Yao, Tai Sing Lee, Jiayi Hong, Yang Li, Hongfei Jiang, Ian Max Andolina, Shiming Tang:
A large calcium-imaging dataset reveals a systematic V4 organization for natural scenes. CoRR abs/2307.00932 (2023) - [i10]Ziqi Wen, Tianqin Li, Tai Sing Lee:
Does resistance to Style-Transfer equal Shape Bias? Evaluating Shape Bias by Distorted Shape. CoRR abs/2310.07555 (2023) - [i9]Tianqin Li, Ziqi Wen, Yangfan Li, Tai Sing Lee:
Emergence of Shape Bias in Convolutional Neural Networks through Activation Sparsity. CoRR abs/2310.18894 (2023) - 2022
- [c20]Tianqin Li, Zijie Li, Andrew Luo, Harold Rockwell
Prototype memory and attention mechanisms for few shot image generation. ICLR 2022 - [i8]Andrew Luo, Tianqin Li, Wen-Hao Zhang, Tai Sing Lee:
SurfGen: Adversarial 3D Shape Synthesis with Explicit Surface Discriminators. CoRR abs/2201.00112 (2022) - [i7]Nikolas McNeal, Jennifer Huang, Aniekan Umoren, Shuqi Dai, Roger B. Dannenberg, Richard Randall, Tai Sing Lee:
Relating Human Perception of Musicality to Prediction in a Predictive Coding Model. CoRR abs/2210.16587 (2022) - 2021
- [j15]Ziniu Wu, Harold Rockwell
Complexity and diversity in sparse code priors improve receptive field characterization of Macaque V1 neurons. PLoS Comput. Biol. 17(10) (2021) - [c19]Andrew Luo, Tianqin Li, Wen-Hao Zhang, Tai Sing Lee:
SurfGen: Adversarial 3D Shape Synthesis with Explicit Surface Discriminators. ICCV 2021: 16218-16228 - [i6]Yimeng Zhang, Harold Rockwell, Sicheng Dai, Ge Huang, Stephen Tsou, Yuanyuan Wei
Recurrent networks improve neural response prediction and provide insights into underlying cortical circuits. CoRR abs/2110.00825 (2021)
2010 – 2019
- 2019
- [j14]Yimeng Zhang
Convolutional neural network models of V1 responses to complex patterns. J. Comput. Neurosci. 46(1): 33-54 (2019) - [c18]Wenhao Zhang, Si Wu, Brent Doiron, Tai Sing Lee:
A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits. NeurIPS 2019: 3799-3808 - [i5]Siming Yan, Xuyang Fang, Bowen Xiao, Harold Rockwell, Yimeng Zhang, Tai Sing Lee:
Recurrent Feedback Improves Feedforward Representations in Deep Neural Networks. CoRR abs/1912.10489 (2019) - 2017
- [c17]Heqing Ya, Haonan Sun, Jeffrey Helt, Tai Sing Lee:
Learning to Associate Words and Images Using a Large-Scale Graph. CRV 2017: 16-23 - [c16]Hao Wang, Xingyu Lin, Yimeng Zhang, Tai Sing Lee:
Learning Robust Object Recognition Using Composed Scenes from Generative Models. CRV 2017: 232-239 - [c15]Xingyu Lin, Hao Wang, Zhihao Li, Yimeng Zhang, Alan L. Yuille, Tai Sing Lee:
Transfer of View-manifold Learning to Similarity Perception of Novel Objects. ICLR (Poster) 2017 - [i4]Xingyu Lin, Hao Wang, Zhihao Li, Yimeng Zhang, Alan L. Yuille, Tai Sing Lee:
Transfer of View-manifold Learning to Similarity Perception of Novel Objects. CoRR abs/1704.00033 (2017) - [i3]Hao Wang, Xingyu Lin, Yimeng Zhang, Tai Sing Lee:
Learning Robust Object Recognition Using Composed Scenes from Generative Models. CoRR abs/1705.07594 (2017) - [i2]Heqing Ya, Haonan Sun, Jeffrey Helt, Tai Sing Lee:
Learning to Associate Words and Images Using a Large-scale Graph. CoRR abs/1705.07768 (2017) - 2015
- [j13]Xiong Li, Bin Wang, Yuncai Liu, Tai Sing Lee:
Stochastic feature mapping for PAC-Bayes classification. Mach. Learn. 101(1-3): 5-33 (2015) - [c14]Mingmin Zhao, Chengxu Zhuang, Yizhou Wang, Tai Sing Lee:
Predictive Encoding of Contextual Relationships for Perceptual Inference, Interpolation and Prediction. ICLR (Workshop) 2015 - 2014
- [j12]Jason M. Samonds
Sample Skewness as a Statistical Measurement of Neuronal Tuning Sharpness. Neural Comput. 26(5): 860-906 (2014) - 2013
- [c13]Xiong Li, Bin Wang, Yuncai Liu, Tai Sing Lee:
Learning Discriminative Sufficient Statistics Score Space for Classification. ECML/PKDD (3) 2013: 49-64 - 2012
- [i1]Xiong Li, Tai Sing Lee, Yuncai Liu:
Stochastic Feature Mapping for PAC-Bayes Classification. CoRR abs/1204.2609 (2012) - 2011
- [c12]Xiong Li, Tai Sing Lee, Yuncai Liu:
Hybrid generative-discriminative classification using posterior divergence. CVPR 2011: 2713-2720 - 2010
- [j11]Ryan C. Kelly, Matthew A. Smith
Local field potentials indicate network state and account for neuronal response variability. J. Comput. Neurosci. 29(3): 567-579 (2010) - [c11]Ryan C. Kelly, Matthew A. Smith, Robert E. Kass, Tai Sing Lee:
Accounting for network effects in neuronal responses using L1 regularized point process models. NIPS 2010: 1099-1107
2000 – 2009
- 2009
- [c10]Thomas S. Stepleton, Zoubin Ghahramani, Geoffrey J. Gordon, Tai Sing Lee:
The Block Diagonal Infinite Hidden Markov Model. AISTATS 2009: 552-559 - 2008
- [j10]Brian Potetz, Tai Sing Lee:
Efficient belief propagation for higher-order cliques using linear constraint nodes. Comput. Vis. Image Underst. 112(1): 39-54 (2008) - 2006
- [c9]Jason M. Samonds, Brian Potetz, Tai Sing Lee:
Neurophysiological Evidence of Cooperative Mechanisms for Stereo Computation. NIPS 2006: 1201-1208 - 2005
- [j9]Yuguo Yu
Adaptive contrast gain control and information maximization. Neurocomputing 65-66: 111-116 (2005) - [c8]Brian Potetz, Tai Sing Lee:
Scaling Laws in Natural Scenes and the Inference of 3D Shape. NIPS 2005: 1089-1096 - [c7]Thomas S. Stepleton, Tai Sing Lee:
Using Co-Occurrence and Segmentation to Learn Feature-Based Object Models from Video. WACV/MOTION 2005: 129-134 - 2004
- [j8]Ryan C. Kelly, Tai Sing Lee:
Decoding visual input from V1 neuronal activity with particle filtering. Neurocomputing 58-60: 849-855 (2004) - 2003
- [j7]Richard Romero, Yuguo Yu, Pedram Afshar, Tai Sing Lee:
Adaptation of the temporal receptive fields of macaque V1 neurons. Neurocomputing 52-54: 135-140 (2003) - [j6]Yuguo Yu
Adaptation of the transfer function of the Hodgkin-Huxley (HH) neuronal model. Neurocomputing 52-54: 441-445 (2003) - [c6]Ryan C. Kelly, Tai Sing Lee:
Decoding V1 Neuronal Activity using Particle Filtering with Volterra Kernels. NIPS 2003: 1359-1366 - 2002
- [j5]Richard Romero, Tai Sing Lee:
Spike train analysis for single trial data. Neurocomputing 44-46: 597-603 (2002) - [j4]Gustavo Deco, Tai Sing Lee:
A unified model of spatial and object attention based on inter-cortical biased competition. Neurocomputing 44-46: 775-781 (2002) - 2001
- [c5]Stella X. Yu, Tai Sing Lee, Takeo Kanade:
A Hierarchical Markov Random Field Model for Figure-Ground Segregation. EMMCVPR 2001: 118-133 - 2000
- [j3]Stella X. Yu, Tai Sing Lee:
What do V1 neurons tell us about saccadic suppression? Neurocomputing 32-33: 271-277 (2000) - [j2]Elise Cassidente, Xiaogang Yan, Tai Sing Lee:
A Bayesian decision approach to evaluate local and contextual information in spike trains. Neurocomputing 32-33: 1013-1020 (2000)
1990 – 1999
- 1999
- [c4]Tai Sing Lee, Stella X. Yu:
An Information-Theoretic Framework for Understanding Saccadic Eye Movements. NIPS 1999: 834-840 - 1996
- [j1]Tai Sing Lee:
Image Representation Using 2D Gabor Wavelets. IEEE Trans. Pattern Anal. Mach. Intell. 18(10): 959-971 (1996) - 1995
- [c3]Song Chun Zhu, Tai Sing Lee, Alan L. Yuille
Region Competition: Unifying Snakes, Region Growing, Energy/Bayes/MDL for Multi-band Image Segmentation. ICCV 1995: 416- - 1994
- [c2]Tai Sing Lee:
Representational Strategy in the Visual Cortex. ICIP (2) 1994: 590-594 - 1992
- [c1]Tai Sing Lee, David Mumford, Alan L. Yuille
Texture Segmentation by Minimizing Vector-Valued Energy Functionals: The Coupled-Membrane Model. ECCV 1992: 165-173
Coauthor Index
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