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2024
Peng, Y., Burling, J. M., Todorova, G. K., Neary, C., Pollick, F. E., and Lu, H. (in press), Patterns of Saliency and Semantic Features Distinguish Gaze of Expert and Novice Viewers of Surveillance Footage. Psychonomic Bulletin & Review.
Jiang, Y., Dale, R., & Lu, H. (2024). Transformability, generalizability, but limited diffusibility: Comparing global vs. task-specific language representations in deep neural networks. Cognitive Systems Research, 83, 101184. [PDF]
2023
Ichien, N., Liu, Q., Fu, S., Holyoak, K.J., Yuille, A.L. and Lu, H. (2023), Two Computational Approaches to Visual Analogy: Task-Specific Models Versus Domain-General Mapping. Cognitive Science, 47: e13347. [PDF]
Chen, Y. C., Pollick, F., & Lu, H. (2023). Aesthetic preferences for prototypical movements in human actions. Cognitive Research: Principles and Implications, 8(1), 1-13. [PDF]
Webb, T., Fu, S., Bihl, T., Holyoak, K. J., & Lu, H. (2023). Zero-shot visual reasoning through probabilistic analogical mapping. Nature Communications, 14(1), 5144. [PDF]
Webb, T., Holyoak, K. J., & Lu, H. (2023). Emergent Analogical Reasoning in Large Language Models. Nature Human Behavior. 7, 1526–1541. [PDF] [ArXiv]
Combs, K., Lu, H., & Bihl, T. J. (2023). Transfer Learning and Analogical Inference: A Critical Comparison of Algorithms, Methods, and Applications. Algorithms, 16(3), 146. [PDF]
Ichien, N., Alfred, K. L., Baia, S., Kraemer, D. J., Holyoak, K. J., Bunge, S. A., & Lu, H. (2023). Relational and lexical similarity in analogical reasoning and recognition memory: Behavioral evidence and computational evaluation. Cognitive Psychology, 141, 101550. [PDF]
Lee, A., Lu, H., & Holyoak, K. J. (2023). Human relational concept learning on the synthetic visual reasoning test. Proceedings of the 45th Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
Snefjella, B., Yun, Y., Fu, S., & Lu, H. (2023). Human similarity judgments of emojis support alignment of conceptual systems across modalities. Proceedings of the 45th Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
Ichien, N., Lin, N., Holyoak, K. J., & Lu, H. (2023). Asymmetry in similarity and difference judgments results from asymmetry in the complexity of the relations same and different. Proceedings of the 45th Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
Peng, Y., Gong, X., Lu, H., & Fang, F. (2023). Mapping between the human visual system and two-stream DCNNs in action representation. Proceedings of the 45th Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
2022
Yuan, L., Gao, X., Zheng, Z., Edmonds, M., Wu, Y.N., Rossano, F., Lu, H., Zhu, Y. and Zhu, S.C. (2022). In situ bidirectional human-robot value alignment. Science Robotics, 7(68), eabm4183. [PDF]
Holyoak, K. J., Ichien, N., & Lu, H. (2022). From semantic vectors to analogical mapping. Current Directions in Psychological Science, 31(4), 355-361. [PDF]
Chen, Y., Pollick, F., & Lu, H. (2022). Aesthetic preferences for causality in biological movements arise from visual processes. Psychonomic Bulletin & Review, 29(5), 1803-1811. [PDF]
Lu, H., Ichien, N., & Holyoak, K. J. (2022). Probabilistic analogical mapping with semantic relation networks. Psychological Review, 129(5), 1078-1103. [PDF]
Gao, X., Yuan, L., Shu, T., Lu, H., & Zhu, S. C. (2022). Show Me What You Can Do: Capability Calibration on Reachable Workspace for Human-Robot Collaboration. IEEE Robotics and Automation Letters. [PDF]
Ichien, N., Lu, H., & Holyoak, K. J. (2022). Predicting patterns of similarity among abstract semantic relations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 48(1), 108–121. https://doi.org/10.1037/xlm0001010. [PDF]
Fu, S., Holyoak, K. J., & Lu, H. (2022). From vision to reasoning: Probabilistic analogical mapping between 3D objects. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
Ichien, N., Alfred, K. L., Baia, S., Kraemer, D. J. M., Bunge, S. A., Lu, H., & Holyoak, K. J. (2022). Relation representations in analogical reasoning and recognition memory. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
Ichien, N., Kan, A., Holyoak, K. J., & Lu, H. (2022). Generative inferences in relational and analogical reasoning: A comparison of computational models. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
Ionescu, A., Lu, H., Holyoak, K. J., & Sandhofer, C. M. (2022). Children’s acquisition of the concept of antonym across different lexical classes. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
Linford, B., Ichien, N., Holyoak, K. J., & Lu, H. (2022). Impact of semantic representations on analogical mapping with transitive relations. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
Snefjella, B., Ichien, N., Holyoak, K. J., & Lu, H. (2022). Predicting human judgments of relational similarity: comparison of computational models based on vector representations of meaning. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
2021
Akula, A. R., Wang, K., Liu, C., Saba-Sadiya, S., Lu, H., Todorovic, S., Chia, J., & Zhu, S. C. (2021). CX-ToM: Counterfactual explanations with theory-of-mind for enhancing human trust in image recognition models. iScience, 103581. [PDF]
Peng, Y., Lu, H., & Johnson, S. P. (2021). Infant perception of causal motion produced by human and inanimate objects. Infant Behavior and Development. 10.1016/j.infbeh.2021.101615. [PDF]
Shu, T., Peng, Y., Zhu, S., Lu, H. (2021). A unified psychological space for human perception of physical and social events. Cognitive Psychology, 128, 101398. [PDF]
Lee, A. L. F, Liu, Z., & Lu, H. (2021). Parts beget parts: Bootstrapping hierarchical object representations through visual statistical learning. Cognition, 209, 104515. [PDF]
Holyoak, K. J., & Lu, H. (2021). Emergence of relational reasoning. Current Opinion in Behavioral Sciences, 37, 118-124. [PDF]
Peng, Y., Lee, H., Shu, T., & Lu, H. (2021). Exploring biological motion perception in two-stream convolutional neural networks. Vision Research, 178, 28-40. [PDF]
Chiang, J. N., Peng, Y., Lu, H., Holyoak, K. J., & Monti, M. M. (2021). Distributed code for semantic relations predicts neural similarity during analogical reasoning. Journal of Cognitive Neuroscience, 33(3), 377-389. [PDF]
Ichien, N., Liu, Q., Fu, S., Holyoak, K. J., Yuille, A., & Lu, H. (2021). Visual analogy: deep learning versus compositional models. Proceedings of the 43rd Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
Chen, Y., Pollick, F., & Lu, H. (2021). Aesthetic experience is influenced by causality in biological movements. Proceedings of the 43rd Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
Priniski, J.H., Mokhberian, N., Harandizadeh, B., Morstatter, F., Lerman, K., Lu, H., Brantingham, P.J. (2021), Mapping Moral Valence of Tweets Following the Killing of George Floyd. 6th International Workshop on Social Sensing. [PDF]
2020
Baker, N., Lu, H., Erlikhman, G., & Kellman, P. (2020). Local features and global shape information in object classification by deep convolutional neural networks. Vision Research. 172, 46-61. [PDF]
Kadambi, A., Ichien, N., Qiu, S. & Lu, H. (2020).Understanding the visual perception of awkwardness: How greetings go awry. Attention, Perception, & Psychophysics. 1-14. [PDF]
Ichien, N., Lu, H., & Holyoak, K. (2020). Verbal analogy problem sets: an inventory of testing materials. Behavior Research Methods. 1-14. [PDF] [Verbal Analogy Dataset]
Peng, Y. Ichien, N., & Lu, H. (2020). Causal actions enhance perception of continuous body movements. Cognition, 194. [PDF ] [LINK] [DEMO]
Edmonds, M., Ma, X., Qi, S., Zhu, Y., Lu, H., & Zhu, S. C. (2020, April). Theory-based causal transfer: Integrating instance-level induction and abstract-level structure learning. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 34, No. 02, pp. 1283-1291). [PDF]
Schorn, J. M., Lu, H., & Knowlton, B. J. (2020) Contextual Interference Effect in Motor Skill Learning: An Empirical and Computational Investigation. Proceedings of the 42nd Annual Meeting of the Cognitive Science Society. Cognitive Science Society. [PDF]
2019
Edmonds, M., Gao, F., Liu, H., Xie, X., Qi, S., Rothrock, B., Zhu, Y., Wu, Y. N., Lu, H., & Zhu, S. C. (2019). A tale of two explanations: Enhancing human trust by explaining robot behavior. Science Robotics, 4(37). [PDF]
Lu, H., Wu, Y, & Holyoak, K.H. (2019). Emergence of analogy from relation learning. Proceedings of the National Academy of Sciences, 116, 4176-4181. [PDF] [Supplemental materials] [MATLAB code]
Burling, J. M., Kadambi, A., Safari, T., & Lu, H. (2019). The impact of autistic traits on self-recognition of body movements. Frontiers in Psychology, 9, 2687. [PDF] [DEMO]
Zhang, C., Jia, B., Gao, F., Zhu, Y., Lu, H., & Zhu, S. C. (2019). Learning perceptual inference by contrasting. In Advances in Neural Information Processing Systems, 1073-1085. [PDF]
Shu, T., Peng, Y, Lu, H. & Zhu, S. (2019). Partitioning the perception of physical and social events with a unified psychological space. Proceedings of the 41st Annual Meeting of the Cognitive Science Society. Montreal, Canada: Cognitive Science Society. [PDF] [DEMO]
Edmonds, M., Qi, S., Zhu, Y., Kubricht, J., Zhu, S., & Lu, H. (2019). Decomposing human causal leanring: bottom-up associative learning and top-down schema reasoning. Proceedings of the 41st Annual Meeting of the Cognitive Science Society. Montreal, Canada: Cognitive Science Society. [PDF] [DEMO]
Kadambi, A. & Lu, H. (2019). Individual differences in self-recognition from body movements. Proceedings of the 41st Annual Meeting of the Cognitive Science Society. Montreal, Canada: Cognitive Science Society. [PDF]
Lu, H., Liu, Q., Ichien, N., Yuille, A., & Holyoak, K. (2019). Seeing the meaning: vision meets semantics in solving pictorial analogy problems. Proceedings of the 41st Annual Meeting of the Cognitive Science Society. Montreal, Canada: Cognitive Science Society. [PDF]
Peng, Y., Ichien, N., & Lu, H. (2019). Perception of continuous movements from causal actions. Proceedings of the 41st Annual Meeting of the Cognitive Science Society. Montreal, Canada: Cognitive Science Society. [PDF]
2018
Baker, N., Lu, H, Erlikhman, G. & Kellman, P. J. (2018). Deep convolutional networks do not classify based on global object shape. PLoS Computational Biology, 14(12). [PDF]
Keane, B., Peng, Y., Demmin, D., Silverstein, S. M., & Lu, H. (2018). Intact perception of coherent motion, dynamic rigid form, and biological motion in chronic schizophrenia. Psychiatry Research, 268, 53-59. [PDF] [DEMO]
Baker, N., Erlikhman, G., Kellman, P., & Lu, H. (2018). Deep convoutional networks do not perceive illusory contours. Proceedings of the 40th Annual Meeting of the Cognitive Science Society. Madison, WI: Cognitive Science Society. [PDF]
Peng, Y., Javangula, R., Lu, H. & Holyoak, K. (2018). Behaviroal oscillations in verification of relational role bindings. Proceedings of the 40th Annual Meeting of the Cognitive Science Society. Madison, WI: Cognitive Science Society. [PDF]
Kubricht, J., & Lu, H. (2018). Physical and causal judgments for objects collisions depend on relative motion. Proceedings of the 40th Annual Meeting of the Cognitive Science Society. Madison, WI: Cognitive Science Society. [PDF]
Edmonds, M.,Kubricht, J., Summers, C., Zhu, Y., Rothrock, B., Zhu, S. C., & Lu, H. (2018). Human causal transfer: Challenges for deep reinforcement learning. Proceedings of the 40th Annual Meeting of the Cognitive Science Society. Madison, WI: Cognitive Science Society. [PDF]
Wang, D., Kubricht, J., Zhu, Y., Liang, W., Zhu, S. C., Jiang, C., & Lu, H. (2018). Spatially Perturbed Collision Sounds Attenuate Perceived Causality in 3D Launching Events. In IEEE Conference on Virtual Reality and 3D User Interfaces. [PDF]
Shu, T.*, Peng, Y.*, Fan, L., Lu, H. & Zhu, S. (2018). Perception of human interaction based on motion trajectories: from aerial videos to decontextualized animations. Topics in Cognitive Science, 10(1), 225-241. *Equal contributors. [PDF] [DEMO]
Burling, J., & Lu, H. (2018). Categorizing coordination from the perception of joint actions. Attention, Perception, & Psychophysics.80: 7-13. [PDF]
2017
Su, J., & Lu, H. (2017). Flash-lag effects in biological motion interact with body orientation and action. Vision Research. 140, 13-24. [PDF]
Kubricht, J. R., Lu, H., & Holyoak, K. J. (2017). Intuitive physics: current research and controversies. Trends in cognitive sciences. 21(10), 749-759. [PDF]
Lu, H., Tjan, B. S., & Liu, Z. (2017). Human efficiency in detecting and discriminating biological motion. Journal of Vision. 17(6):4, 1-14. [PDF]
Shu, T.*, Peng, Y.*, Fan, L., Lu, H. & Zhu, S. (2017). Inferring human interaction from motion trajectories in aerial videos. Proceedings of the 39th Annual Meeting of the Cognitive Science Society. London, UK: Cognitive Science Society. *Equal contributors. Computational modeling prize in Perception/Action from the Cognitive Science Society. [PDF] [DEMO]
Kubricht, J.*, Zhu, Y.*, Jiang, C.*, Terzopoulos, D., Zhu, S., & Lu, H. (2017). Consistent probabilistic simulation underlying human judgment in substance dynamics. Proceedings of the 39th Annual Meeting of the Cognitive Science Society. London, UK: Cognitive Science Society. *Equal contributors. [PDF]
Lin, J., Zhu, Y., Kubricht, J., Zhu, S., & Lu, H. (2017). Visuomotor adaptation and sensory recalibration in reversed hand movement task. Proceedings of the 39th Annual Meeting of the Cognitive Science Society. London, UK: Cognitive Science Society. [PDF]
Peng, Y., Thurman S., & Lu, H. (2017). Causal action: a fundamental constraint on perception and inference with body movements. Psychological Science, 28(6), 789-807. [PDF] [DEMO]
Ye, T., Qi, S., Kubricht, J., Zhu, Y., Lu, H., Zhu, SC. (2017). The Martian: examining human physical judgments across virtual gravity fields. IEEE Transactions on Visualization and Computer Graphic, 23(4), 1399-1408. [PDF]
Kubricht, J. R., Lu, H., & Holyoak, K. J. (2017). Individual differences in spontaneous analogical transfer. Memory & Cognition. 45, 576-588. [PDF]
van Boxtel, J., Peng, Y., Su, J., & Lu, H. (2017). Individual differences in high-level biological motion tasks correlate with autistic traits. Vision Research. 141, 136-144. [PDF]
Chen, D., Lu, H., & Holyoak, K. J. (2017). Generative inferences based on learned relations. Cognitive Science. 41, 1062-1092. [PDF]
2016
Su, J., van Boxtel, J. A., & Lu, H. (2016). Social interactions receive priority to conscious perception. PLoS ONE. 11(8). doi: 10.1371/journal.pone.0160468 [PDF]
van Boxtel, J., Dapretto, M., & Lu, H. (2016). Intact recognition, but attentuated adaptation, for biological motion in youth with autism spectrum disorder. Autism Research. 9(10), 1103-1113. [PDF]
Thurman, S.M., van Boxtel, J. J. A, Monti, M. M., Chiang, J. N., & Lu, H. (2016). Neural adaptation in pSTS correlates with perceptual aftereffects to biological motion and with autistic traits. NeuroImage. 136: 146-61. [PDF]
Kubricht, J., Jiang C., Zhu, Y., Zhu, S-C., Terzopoulos D., & Lu, H. (2016). Probabilistic simulation predicts human performance on viscous water-pouring problem. Proceedings of the 38th Annual Meeting of the Cognitive Science Society. Philadelphia, Pennsylvania: Cognitive Science Society. [PDF]
Shu, T., Thurman, S., Chen, D., Zhu, S-C, & Lu, H. (2016). Critical features of joint actions that signal human interaction. Proceedings of the 38th Annual Meeting of the Cognitive Science Society. Philadelphia, Pennsylvania: Cognitive Science Society. [PDF]
Peng, Y., Thurman, S. & Lu, H. (2016). Causal action: a fundamental constraint on perception of bodily movements. Proceedings of the 38th Annual Meeting of the Cognitive Science Society. Philadelphia, Pennsylvania: Cognitive Science Society. [PDF]
Powell, D., Merrick, A., Lu, H., & Holyoak, K. (2016). Causal competition based on generic priors.Cognitive Psychology, 86, 62-86. [PDF]
Thurman, S. & Lu, H. (2016). A comparison of form processing involved in the perception of biological and non-biological movements. Journal of Vision, 16(1):1, 1-16. [PDF]
Thurman, S. & Lu, H. (2016). Revisiting the importance of common body motion in human action perception. Attention, Perception & Psychophysics, 78(1), 30-36. [PDF]
Lu, H., Rojas, R. R., Beckers, T., & Yuille, A. L. (2016). A Bayesian theory of sequential causal learning and abstract transfer. Cognitive Science. 40(2), 404-39. [PDF] [Supplemental]
2015
Kubricht, J., Lu, H., & Holyoak, K. J. (2015). Animation facilitates source understanding and spontaneous analogical transfer. Proceedings of the 37th Annual Conference of the Cognitive Science Society. [PDF]
Chen, D., Lu, H., & Holyoak, K. J. (2015). Learning and generalizing cross-category relations using hierarchical distributed representations. Proceedings of the 37th Annual Conference of the Cognitive Science Society. [PDF]
van Boxtel, J. & Lu, H. (2015). Understanding biological motion, in Emerging Trends in the Social and Behavioral Sciences (eds.) Robert Scott and Stephen Kosslyn, Hoboken, NJ: John Wiley and Sons.
van Boxtel, J. & Lu, H. (2015). Joints and their relations as critical features in action discrimination: Evidence from a classification image method. Journal of Vision. 15(1):20, 1-17. [PDF]
2014
Thurman, S., & Lu, H. (2014). Perception of social interactions for spatially scrambled biological motion. PLoS ONE. 9(11), 1-12. [PDF]
Powell, D., Merrick, M. A., Lu, H., & Holyoak, K. J. (2014). Generic priors yield competition between independently occurring preventive causes. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 2893-2798). Austin, TX: Cognitive Science Society. [PDF]
Bye, J. K., Nguyen, B. D., Lu, H., & Johnson, S. P. (2014). Anticipating an effect from predictive visual sequences: development of infants’ causal inference from 9 to 18 months. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 1976-1981). Austin, TX: Cognitive Science Society. [PDF]
Chen, D., Lu, H., & Holyoak, K. J. (2014). The discovery and comparison of symbolic magnitudes. Cognitive Psychology, 71 , 27-54. [PDF] [MATLAB code]
Lee, A. L. F., & Lu, H. (2014). Global motion aftereffect does not depend on awareness of the adapting motion direction. Attention, Perception & Psychophysics , 76 (3),766-779. [PDF] (Best Paper Award)
Thurman, S. M., & Lu, H. (2014). Bayesian integration of position and orientation cues in perception of biological and non-biological forms. Frontiers in Human Neuroscience, 8: 91, 1-21. [PDF]
2013
van Boxtel, J. & Lu , H. (2013). A biological motion toolbox for reading, displaying and manipulating motion capture data in research settings . Journal of Vision, 13(12):7, 1-16. [PDF]
Chen, D., Lu, H., & Holyoak, K. J. (2013). Generative inferences based on a discriminative Bayesian model of relation learning. Proceedings of the Thirty-five Annual Conference of the Cognitive Science Society. [PDF]
Powell , D., Merrick, M. A., Lu, H., & Holyoak, K. J. (2013). Generic priors yield competition between independently-occurring causes. Proceedings of the Thirty-five Annual Conference of the Cognitive Science Society. [PDF]
Keane , B., Lu, H., Papathomas, T., Silverstein, S., & Kellman, P. (2013). Reinterpreting behavioral receptive fields: lightness induction alters visually completed shape. PLoS ONE, 8(6), 1-11. [PDF]
Thurman , S. M., & Lu, H. (2013). Physical and biological constraints govern perceived animacy of scrambled human forms. Psychological Science, 24, 1133-1141. [PDF]
Carroll, C., Cheng, P., & Lu, H. (2013). Inferential dependencies in causal inference: A comparison of belief-distribution and associative approaches. Journal of Experimental Psychology: General, 142(3): 845-863. [PDF]
van Boxtel, J. & Lu, H. (2013). Impaired global, and compensatory local, biological motion processing in people with high levels of autistic traits. Frontiers in Psychology, 4:209. doi: 100.3389/fpsyg.2013.00209 [PDF]
van Boxtel , J., & Lu, H. (2013). General commentary: A predictive coding perspective on autism spectrum disorders. Frontiers in Psychology, 4:19. [PDF]
Thurman , S. M. & Lu, H. (2013). Complex interactions between spatial, orientation and motion cues for biological motion perception across visual space. Journal of Vision, 13(2):8, 1-18 . [PDF] [DEMO]
Lu H. (2013). Modeling causal learning. In H. Pashler (Ed.), Encyclopedia of the mind. Thousand Oaks, CA: Sage
2012
Lu, H., Chen, D., & Holyoak, K. J. (2012). Bayesian analogy with relational transformations. Psychological Review, 119(3), 617-648. [PDF] [MATLAB Code]
van Boxtel, J., & Lu, H. (2012). Signature movements lead to efficient search for threatening actions. PLoS ONE , 7(5): e37085, 1-6. doi:10.1371/journal.pone.0037085. [PDF] [Supplemental document]
Lee, A. L. F, & Lu, H. (2012). Two forms of aftereffects induced by transparent motion reveal multilevel adaptation. Journal of Vision, 12(4), 1-13. [PDF]
Keane, B. P., Lu, H., Papathomas, T. V., Silverstein, S. M., & Kellman, P. J. (2012). Is interpolation cognitively encapsulated? Measuring the effects of belief on Kanizsa shape discrimination and illusory contour formation. Cognition, 123, 404-418. [PDF]
2011
van Boxtel, J., & Lu, H. (2011). Visual search by action category. Journal of Vision. 11(7), 1-14. [PDF]
Carroll, C., Cheng, P., & Lu, H. (2011). Uncertainty and dependency in causal inference. Proceedings of the 33 rd Annual Conference of the Cognitive Science Society. Boston, MA: Cognitive Science Society. [PDF].
Holyoak, K. J., & Lu, H. (2011). What the Bayesian framework has contributed to understanding cognition: Causal learning as a case study. Behavioral and Brain Sciences, 34, 203-204. [PDF]
Huang, X., Lu, H., Zhou, Y., & Liu, Z. (2011). General and specific perceptual learning in radial speed discrimination. Journal of Vision. 11(4), 1-11. [PDF]
2010
Lu, H., Lin, T., Lee, A., Vese, L., & Yuille, A. L. (2010). Functional form of motion priors in human motion perception. Advances in Neural Information Processing Systems, 23, 1495-1503. Cambridge, MA: MIT Press. [PDF]
Wu, S., He, X., Lu, H., & Yuille, A. L. (2010). A unified model of short-range and long-range motion perception. Advances in Neural Information Processing Systems , 23, 2478-2486. Cambridge, MA: MIT Press. [PDF]
Holyoak, K. J., Lee, H. S., & Lu, H. (2010). Analogical and category-based inference: A theoretical integration with Bayesian causal models. Journal of Experimental Psychology: General, 139(4), 702-27. [PDF] [MATLAB code]
Lu, H. (2010). Structural processing in biological motion perception. Journal of Vision. 10(12):13, 1-13. [PDF]
Chen, D., Lu, H., & Holyoak, K. J. (2010). Learning and generalization of abstract semantic relations: Preliminary investigation of Bayesian approaches. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. [PDF]
Carroll, C. D., Cheng, P. W., & Lu, H. (2010). Uncertainty in causal inference: The case of retrospective revaluation. Proceedings of the 32nd Annual Conference of the Cognitive Science Society. [PDF]
Lee, A. & Lu, H. (2010). A comparison of global motion perception using a multiple-aperture stimulus. Journal of Vision. 10(4): 9; 1-16. doi:10.1167/10.4.9. [PDF]
2009
Lu, H., Weiden, M., & Yuille, A. (2009). Modeling the spacing effect in sequential category learning. In Y. Bengio and D. Schuurmans and J. Lafferty and C. K. I. Williams & A. Culotta.Advances (Eds.): Advances in Neural Information Processing Systems 22. 1159—1167. [PDF]
Lee, H. S., Holyoak, K. J., & Lu, H. (2009). Integrating analogical inference with Bayesian causal models. In B. Kokinov, D. Gentner, & K. J. Holyoak (Eds.), New frontiers in analogy research: Proceedings of the Second International Conference on Analogy (pp. 300-309). Sofia, Bulgaria: New Bulgarian University.
Lu, H., & Liu, Z. (2009). When a never-seen but less-occluded image is better recognized: Evidence from same-different matching experiments and a model. Journal of Vision, 9(4):4, 1-12. [PDF]
Wu, S., Lu, H., & Yuille, A. (2009). Model selection and parameter estimation in motion perception. In D. Koller , D. Schuurmans, Y. Bengio & L. Bottou (Eds.): Advances in Neural Information Processing Systems, 21, 1793-1800. Cambridge, MA: MIT Press. [PDF]
2008
Lu, H., & Liu, Z. (2008). When a never-seen but less-occluded image is better recognized: Evidence from old-new memory experiments. Journal of Vision, 8 (7), 1-9. [PDF]
Lu, H., Yuille, A., Liljeholm, M., Cheng, P. W., Holyoak, K. J. (2008). Bayesian generic priors for causal learning. Psychological Review, 115(4), 955-984. [PDF] , [MATLAB CODE 1] , [[MATLAB CODE 2] require MATLAB Symbolic Toolbox, but with faster computation]
Lu, H., Rojas, R., Beckers, T., & Yuille, A. (2008). Sequential causal learning in humans and rats. Proceedings of the Twenty-ninth Annual Conference of the Cognitive Science Society. [PDF]
Yuille, A. L., & Lu, H. (2008). The noisy-logical distribution and its application to causal inference. Advances in neural information processing systems, Vol. 20. Cambridge, MA: MIT Press. [PDF]
2007
Keane, B., Lu, H., & Kellman, P (2007). Classification images reveal spatiotemporal contour interpolation. Vision Research , 47, 3460-75. [PDF]
Huang, X., Lu, H., Tjan, B., Zhou, Y., & Liu, Z. (2007). Motion perceptual learning: When only task-relevant information is learned. Journal of Vision, 7(10), 1-10. [PDF]
Lu, H., Yuille, A., Liljeholm, M., Cheng, P. W., & Holyoak, K. J. (2007). Bayesian models of judgments of causal strength: A comparison. In D. S. McNammara & G. Trafton (Eds.), Proceedings of the Twenty-ninth Annual Conference of the Cognitive Science Society (pp. 1241-1246). [PDF]
2006
Lu, H., & Liu, Z. (2006). Computing dynamic classification images from correlation maps. Journal of Vision, 6(4), 475-483. [PDF]
Lu, H., Tjan, B., & Liu, Z. (2006). Shape recognition alters sensitivity in stereoscopic depth discrimination. Journal of Vision, 6(1), 75-78. [PDF]
Lu, H., Yuille, A., Liljeholm, M., Cheng, P. W., & Holyoak, K. J. (2006). Modeling causal learning using Bayesian generic priors on generative and preventive powers. In R. Sun & N. Miyake (Eds.), Proceedings of the Twenty-eighth Annual Conference of the Cognitive Science Society (pp. 519-524). Mahwah, NJ: Erlbaum. [PDF]
Lu, H., Morrison, R. G., Hummel, J. E., & Holyoak, K. J. (2006). Role of gamma-band synchronization in priming of form discrimination for multi-object displays. Journal of Experimental Psychology: Human Perception and Performance, 32, 610-617. [PDF]
Lu, H., & Yuille, A. L. (2006). Ideal observers for detecting motion: Correspondence noise. In B. Schölkopf, J. Platt, & T. Hofmann (Eds.), Advances in neural information processing system s, Vol. 19 (pp. 827-834). Cambridge, MA: MIT Press. [PDF]
Hou, F., Lu, H., Zhou, Y., & Liu, Z. (2006). Amodal completion impairs stereo acuity discrimination. Vision Research, 46(13), 2061-2068. [PDF]
Lu, H., Zavagno, D., & Liu, Z. (2006). The glare effect does not give rise to a longer lasting afterimage. Perception, 35(5), 701-707. [PDF]
2005 & before
Lu, H., Qian, N., & Liu, Z. (2004). Learning motion discrimination with suppressed MT. Vision Research, 44, 1817-1825. [PDF]
Jiar, Y., & Lu, H. (2000). Fish-eye lens camera calibration for high accuracy stereo vision system. Proceedings of SPIE International Society for Optical Engineering, 4117, 280-288.
Lu, H., Jiar, Y. , Liu, W., Zhu, Y., & Xu, A. (2000). Stereo vision using fish-eye lens cameras for dense depth imaging. Proceedings of International Conference on Image and Graphics.
Jiar, Y. , Lu, H., Xu, A., & Liu, W. (2000). Fish-eye lens camera calibration for stereo vision system. Chinese Journal of Computer Science , 23 , 1215-1219.
Jiar, Y. , Lu, H., & Liu, W. (2000). Fish-eye lens camera stereo vision for dense depth map recovery. Chinese Journal of Computer Science , 23 , 1332-1336.
Lu, H., & Jiar, Y. (2000). Dense depth image recovery using multi-baseline stereo system. Journal of Beijing Institute of Technology , 20 , 69-72.
Lu, H., & Jiar, Y. (1998). High resolution depth image recovery using multi-baseline stereo system. Chinese Journal of Robotics , 20 , 460-464.