S. Nikolaidis, D. Hsu, and S. Srinivasa. Human-robot mutual adaptation in collaborative tasks: Models and experiments. Int. J. Robotics Research, 36(5–7):618–634, 2017.
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S. Nikolaidis, Y. Zhu, D. Hsu, and S. Srinivasa. Human-robot mutual adaptation in shared autonomy. In Proc. ACM/IEEE Int. Conf. on Human-Robot Interaction, 2017.
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N. Ye, A. Somani, D. Hsu, and W. Lee. DESPOT: Online POMDP planning with regularization. J. Artificial Intelligence Research, 58:231–266, 2017.
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P. Singh, M. Chen, L. Carlone, S. Karaman, E. Frazzoli, and D. Hsu. Supermodular mean squared error minimization for sensor scheduling in optimal kalman filtering. In Proc. American Control Conf., 2017.
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Z. Lim, D. Hsu, and W. Lee. Shortest path under uncertainty: Exploration versus exploitation. In Proc. Conf. on Uncertainty in Artificial Intelligence, 2017.
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Z. Lan, M. Shridhar, D. Hsu, and S. Zhao. XPose: Reinventing user interaction with flying cameras. In Proc. Robotics: Science & Systems, 2017.
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Y.F. Luo, H.Y. Bai, D. Hsu, and W.S. Lee. Importance sampling for online planning under uncertainty. In Algorithmic Foundations of Robotics XII – Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR). 2016.
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M. Koval, D. Hsu, N. Pollard, and S. Srinivasa. Configuration lattices for planar contact manipulation under uncertainty. In Algorithmic Foundations of Robotics XII – Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR). 2016.
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S. Nikolaidis, A. Kuznetsov, D. Hsu, and S. Srinivasa. Formalizing human-robot mutual adaptation: A bounded memory model. In Proc. ACM/IEEE Int. Conf. on Human-Robot Interaction. 2016.
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Z.W. Lim, D. Hsu, and W.S. Lee. Adaptive informative path planning in metric spacesInt. J. Robotics Research, 35(5):585-598, 2016.
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J.K. Li, D. Hsu, and W.S. Lee. Act to see and see to act: POMDP planning for objects search in clutter. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2016.
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M. Chen, E. Frazzoli, D. Hsu, and W.S. Lee. POMDP-Lite for robust planning under uncertainty. In Proc. IEEE Int. Conf. on Robotics & Automation, 2016.
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H.Y. Bai, S.J. Cai, N. Ye, D. Hsu, and W.S. Lee. Intention-aware online POMDP planning for autonomous driving in a crowd. In Proc. IEEE Int. Conf. on Robotics & Automation, 2015.
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V. Sezer, T. Bandyopadhyay, D. Rus, E. Frazzoli, and D. Hsu. Towards autonomous navigation of unsignalized intersections under uncertainty of human driver intent. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2015.

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Z.W. Lim, D. Hsu, and W.S. Lee. Adaptive stochastic optimization: from sets to paths. In Advances in Neural Information Processing Systems, 2015.
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Z. Zhang, D. Hsu, W.S. Lee, Z.W. Lim, and A. Bai. PLEASE: Palm leaf search for POMDPs with large observation spaces. In Proc. Int. Conf. on Automated Planning & Scheduling, 2015.
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A. Kupcsik, D. Hsu, and W.S. Lee. Learning dynamic robot-to-human object handover from human feedback. In Proc. Int. Symp. on Robotics Research, 2015.
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K. Wu, W.S. Lee, and D. Hsu. POMDP to the rescue: Boosting performance for Robocup rescue. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2015.
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G.M. Gyori, G. Venkatachalam, P.S. Thiagarajan, D. Hsu, and M.V. Clement. OpenComet: An automated tool for comet assay image analysisRedox Biology, 2(2):457–465, 2014.
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X.X. Wang, Y. Wang, D. Hsu, and Y. Wang. Exploration in interactive personalized music recommendation: A reinforcement learning approachACM Trans. on Multimedia Computing, Communications & Applications, 11(1), 2014.
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Z.W. Lim, D. Hsu, and W.S. Lee. Adaptive informative path planning in metric spaces. In Algorithmic Foundations of Robotics XI—Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR). 2014.
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Z. Zhang, D. Hsu, and L.S. Lee. Covering number for efficient heuristic-based POMDP planning. In Proc. Int. Conf. on Machine Learning. 2014.
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H.Y. Bai, D. Hsu, and W.S. Lee. Integrated perception and planning in the continuous space: A POMDP approachInt. J. Robotics Research, 33(9):1288–1302, 2014.
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S.K. Palaniappan, B.M. Gyori, B. Liu, D. Hsu, and P.S. Thiagarajan. Statistical model checking based calibration and analysis of bio-pathway models. In Proc. Conf. on Computational Methods in Systems Biology, 2013.
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H.Y. Bai, D. Hsu, and W.S. Lee. Planning how to learn. In Proc. IEEE Int. Conf. on Robotics & Automation, 2013.
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P. Chaudhari, S. Karaman, D. Hsu, and E. Frazzoli. Sampling-based algorithms for continuous-time POMDPs. In Proc. American Control Conf., 2013.
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H.Y. Bai, D. Hsu, and W.S. Lee. Integrated perception and planning in the continuous space: A POMDP approach. In Proc. Robotics: Science and Systems, 2013.
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A. Somani, N. Ye, D. Hsu, and W.S. Lee. DESPOT: Online POMDP planning with regularization. In Advances in Neural Information Processing Systems (NIPS). 2013.
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B. Gipson, D. Hsu, L.E. Kavraki, and J.C. Latombe. Computational models of protein kinematics and dynamics: Beyond simulationAnnu. Rev. Anal. Chem, 5:273–291, 2012. DOI: 10.1146/annurev-anchem-062011-143024.
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Y. Wang, K.S. Won, D. Hsu, and W.S. Lee. Monte Carlo Bayesian reinforcement learning. In Proc. Int. Conf. on Machine Learning, 2012.
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T. Bandyopadhyay, K.S. Won, E. Frazzoli, D. Hsu, W.S. Lee, and D. Rus. Intention-aware motion planning. In Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR), 2012.
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B. Liu, J. Zhang, P.Y. Tan, D. Hsu, A.M. Blom, B. Leong, S. Sethi, B. Ho, J.L. Ding, and P.S. Thiagarajan. A computational and experimental study of the regulatory mechanisms of the complement systemPloS Computational Biology, 7(1), 2011.
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B. Liu, D. Hsu, and P. S. Thiagarajan. Probabilistic approximations of ODEs-based bio-pathway dynamicsTheoretical Computer Science, 412(21):2188-2206, 2011.
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G. Koh, D. Hsu, and P. S. Thiagarajan. Component-based construction of bio-pathway models: The parameter estimation problemTheoretical Computer Science, 412(26):2840–2853, 2011.
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H.Y. Bai and D. Hsu and Mykel J. Kochenderfer and W.S. Lee. Unmanned aircraft collision avoidance using continuous-state POMDPs. In Proc. Robotics: Science and Systems, 2011.
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T.H.D. Nguyen and D. Hsu and W.S. Lee and T.Y. Leong and L.P. Kaelbling and T. Lozano-Perez and A.H. Grant. CAPIR: Collaborative action planning with intention recognitionProc. AI and Interactive Digital Entertainment Conference, 2011.
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H. Kurniawati and Y. Du and D. Hsu and W.S. Lee. Motion planning under uncertainty for robotic tasks with long time horizonsInt. J. Robotics Research, 30(3):308-323, 2011.
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Z.W. Lim, D. Hsu, and W.S. Lee. Monte Carlo value iteration with macro-actions. In Advances in Neural Information Processing Systems (NIPS), 2011.
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G. Koh, D. Hsu, and P.S. Thiagarajan. Incremental signaling pathway modeling by data integration. In Proc. ACM Int. Conf. on Computational Biology (RECOMB), 2010.
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T.-H. Chiang, D. Hsu, and J.C. Latombe. Markov dynamic models for long-timescale protein motionBioinformatics, 26(12):i269–i277, 2010. Special issue on Int. Conf. on Intelligent Systems for Molecular Biology (ISMB) 2010.
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Y.Z. Du, D. Hsu, H. Kurniawati, W.S. Lee, S.C.W. Ong, and S.W. Png. A POMDP Approach to Robot Motion Planning under Uncertainty. In Int. Conf. on Automated Planning & Scheduling, Workshop on Solving Real-World POMDP Problems, 2010.
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L.L. Ko, D. Hsu, W.S. Lee, and S.C.W. Ong. Structured parameter elicitation. In Proc. AAAI Conf. on Artificial Intelligence, 2010.
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S.C.W. Ong, S.W. Png, D. Hsu, and W.S. Lee. Planning under Uncertainty for Robotic Tasks with Mixed ObservabilityInt. J. Robotics Research, 29(8):1053–1068, 2010.
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H.Y. Bai and D. Hsu and W.S. Lee and V.A. Ngo. Monte Carlo value iteration for continuous-state POMDPs. In D. Hsu et al., editors, Algorithmic Foundations of Robotics IX—Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR), 2010.
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B. Liu, P.S. Thiagarajan, and D. Hsu . Probabilistic approximations of signaling pathway dynamics. In Proc. Conf. on Computational Methods in Systems Biology, 2009.
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B. Liu, P.S. Thiagarajan, and D. Hsu. Probabilistic approximations of bio-pathway dynamics. In ACM Int. Conf. on Computational Biology (RECOMB) Poster Book, 2009.
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S.C.W. Ong, D. Hsu, W.S. Lee, and H. Kurniawati. Partially observable Markov decision process POMDP technologies for sign language based human-computer interaction. In Proc. Int. Conf. on Human-Computer Interaction, 2009.
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S.C.W. Ong, S.W. Png, D. Hsu, and W.S. Lee. POMDPs for robotic tasks with mixed observability. In Proc. Robotics: Science and Systems, 2009.
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H. Kurniawati, Y. Du, D. Hsu, and W.S. Lee. Motion planning under uncertainty for robotic tasks with long time horizons. In Proc. Int. Symp. on Robotics Research, 2009.
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T. Bandyopadhyay, N. Rong, Ang Jr., M.H., D. Hsu, and W.S. Lee. Motion planning for people tracking in uncertain and dynamic environments. In IEEE Int. Conf. on Robotics & Automation, Workshop on People Detection & Tracking, 2009.
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G. Koh, D. Hsu, and P.S. Thiagarajan. Composition of signaling pathway models and its application to parameter estimation. In ACM Int. Conf. on Computational Biology (RECOMB) Poster Book, 2008.
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A. Nigham, L. Tucker-Kellogg, I. Mihalek, C. Verma, and D. Hsu. pFlexAna: Detecting conformational changes in remotely related proteinsNucleic Acids Res., 36:W246–W251, 2008. DOI: 10.1093/nar/gkn259.
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A. Nigham and D. Hsu. Protein conformational flexibility analysis with noisy data. J. Computational Biology, 15(7):813–828, 2008.
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D. Hsu, W.S. Lee, and N. Rong. What makes some POMDP problems easy to approximate?In Advances in Neural Information Processing Systems (NIPS), 2007.
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H. Kurniawati, D. Hsu, and W.S. Lee. SARSOP: Efficient point-based POMDP planning by approximating optimally reachable belief spaces. In Proc. Robotics: Science and Systems, 2008.
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D. Hsu, W.S. Lee, and N. Rong. A point-based POMDP planner for target tracking. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 2644–2650, 2008.
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T. Bandyopadhyay, D. Hsu, and Ang Jr., M.H.. Motion strategies for people tracking in cluttered dynamic environments. In Proc. Int. Symp. on Experimental Robotics, 2008.
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L.J. Guibas, D. Hsu, H. Kurniawati, and E. Rehman. Bounded uncertainty roadmaps for path planning. In Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR), 2008.
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G. Koh, L. Tucker-Kellogg, D. Hsu, and P.S. Thiagarajan. Globally consistent pathway parameter estimates through belief propagationIn Proc. Workshop on Algorithms in Bioinformatics (WABI), 2007.
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A. Nigham and D. Hsu. Protein conformational flexibility analysis with noisy data. In Proc. ACM Int. Conf. on Computational Biology (RECOMB), pp. 396–411, 2007.
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T.-H. Chiang, M.S. Apaydin, D.L. Brutlag, D. Hsu, and J.C. Latombe. Using stochastic roadmap simulation to predict experimental quantities in protein folding kinetics: Folding rates and phi-valuesJ. Computational Biology, 14(5):578–593, 2007.
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D. Hsu, W.S. Lee, and N. Rong. Accelerating point-based POMDP algorithms through successive approximations of the optimal reachable space. Technical Report TRA4/07, National University of Singapore. School of Computing, 2007.
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T. Bandyopadhyay, Ang Jr., M.H., and D. Hsu. Motion planning for 3-D target tracking among obstacles. In Proc. Int. Symp. on Robotics Research, 2007.
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X. Wu, D. Hsu, and A.K.H. Tung. Efficient constrained Delaunay triangulation for large spatial databases. Technical Report TRA1/06, National University of Singapore, School of Computing, 2006.
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G. Koh, H.F.C. Teong, M.-V. Clément, D. Hsu, and P.S. Thiagarajan. A decompositional approach to parameter estimation in pathway modeling: A case study of the Akt and MAPK pathways and their crosstalkBioinformatics, 22(14):271–280, 2006. Special issue on Int. Conf. on Intelligent Systems for Molecular Biology (ISMB) 2006.
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T.-H. Chiang, M.S. Apaydin, D.L. Brutlag, D. Hsu, and J.C. Latombe. Predicting experimental quantities in protein folding kinetics using stochastic roadmap simulation. In Proc. ACM Int. Conf. on Computational Biology (RECOMB), pp. 410–424, Springer, 2006.
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T. Bandyopadhyay, Y.P. Li, Ang Jr., M.H., and D. Hsu. A greedy strategy for tracking a locally predictable target among obstacles. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 2342–2347, 2006.
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H. Kurniawati and D. Hsu. Workspace-based connectivity oracle: An adaptive sampling strategy for PRM planning. In S. Akella and others, editors, Proc. Int. Workshop on the Algorithmic Foundations of Robotics (WAFR), Springer, 2006.
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H.-L. Cheng, D. Hsu, J.-C. Latombe, and G. Sánchez-Ante. Multi-level free-space dilation for sampling narrow passages in PRM planning. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 1255–1260, 2006.
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D. Hsu, J.C. Latombe, and H. Kurniawati. On the probabilistic foundations of probabilistic roadmap planningInt. J. Robotics Research, 25(7):627–643, 2006.
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H.H. González-Baños, D. Hsu, and J.C. Latombe. Motion planning: Recent developments. In S.S. Ge and F.L. Lewis, editors, Autonomous Mobile Robots: Sensing, Control, Decision-Making and Applications, CRC Press, 2006.
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J. Yin, Y. Wang, and D. Hsu. Digital violin tutor: An integrated system for beginning violin learners. In Proc. ACM Multimedia, pp. 976–985, 2005.
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Z. Sun, D. Hsu, T. Jiang, H. Kurniawati, and J. Reif. Narrow passage sampling for probabilistic roadmap plannersIEEE Trans. on Robotics, 21(6):1105–1115, 2005.
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D. Hsu, G. Sánchez-Ante, and Z. Sun. Hybrid PRM sampling with a cost-sensitive adaptive strategy. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 3885–3891, 2005.
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D. Hsu, J.C. Latombe, and H. Kurniawati. On the probabilistic foundations of probabilistic roadmap planning. In Proc. Int. Symp. on Robotics Research, 2005.
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M. Erdmann, D. Hsu, M. Overmars, and F. van der Stappen, editors. Algorithmic Foundations of Robotics VI, Springer, 2005.
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C. Xia, D. Hsu, and A.K.H. Tung. A fast filter for obstructed nearest neighbour queries. In Proc. British National Conferences on Databases, 2004.
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T. Bandyopadhyay, Y.P. Li, Ang Jr., M.H., and D. Hsu. Stealth tracking of an unpredictable target among obstacles. In M. Erdmann and others, editors, Algorithmic Foundations of Robotics VI—Proc. Workshop on the Algorithmic Foundations of Robotics (WAFR), pp. 43–58, Springer, 2004.
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J. Yin, A. Dhanik, D. Hsu, and Y. Wang. The creation of a music-driven digital violinist. In Proc. ACM Multimedia, pp. 476–479, 2004.
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H. Kurniawati and D. Hsu. Workspace importance sampling for probabilistic roadmap planning. In Proc. IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, pp. 1618–1623, 2004.
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D. Hsu and Z. Sun. Adaptive hybrid sampling for probabilistic roadmap planningTechnical Report TRA5/04, National University of Singapore, School of Computing, 2004.
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D. Hsu and Z. Sun. Adaptively combining multiple sampling strategies for probabilistic roadmap planning. In Proc. IEEE Conf. on Robotics, Automation, and Mechatronics, pp. 774–779, 2004.
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M.S. Apaydin, D.L. Brutlag, C. Guestrin, D. Hsu, J.C. Latombe, and C. Varma. Stochastic roadmap simulation: an efficient representation and algorithm for analyzing molecular motionJ. Computational Biology, 10(3-4):247–281, 2003.
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D. Hsu, T. Jiang, J. Reif, and Z. Sun. The bridge test for sampling narrow passages with probabilistic roadmap planners. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 4420–4426, 2003.
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D. Brutlag, M.S. Apaydin, C. Guestrin, D. Hsu, C. Varma, A. Singh, and J.-C. Latombe. Using robotics to fold proteins and dock ligandsBioinformatics, 18:S74–S83, 2002.
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R.-P. Berretty, D. Hsu, L. Kettner, A. Mascarenhas, M.R. Redinbo, and J. Snoeyink. Ligand binding to the pregnane X receptor by geometric matching of hydrogen bonding. In L. Florea and others, editors, Currents in Computational Molecular Biology, pp. 22–23, 2002. The booklet contains extended poster abstracts from RECOMB 2002.
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M.S. Apaydin, D.L. Brutlag, C. Guestrin, D. Hsu, and J.C. Latombe. Stochastic conformational roadmaps for computing ensemble properties of molecular motion. In J.-D. Boissonnat and others, editors, Algorithmic Foundations of Robotics V—Proc. Workshop on the Algorithmic Foundations of Robotics (WAFR), pp. 131–148, Springer, 2002.
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M.S. Apaydin, D.L. Brutlag, C. Guestrin, D. Hsu, and J.C. Latombe. Stochastic roadmap simulation: An efficient representation and algorithm for analyzing molecular motion. In Proc. ACM Int. Conf. on Computational Biology (RECOMB), pp. 12–21, 2002.
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D. Hsu, R. Kindel, J.C. Latombe, and S. Rock. Randomized kinodynamic motion planning with moving obstaclesInt. J. Robotics Research, 21(3):233–255, 2002.
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J. Basch, L.J. Guibas, D. Hsu, and A.T. Nguyen. Disconnection proofs for motion planning. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 1765–1772, 2001.
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L.J. Guibas, D. Hsu, and L. Zhang. A hierarchical method for real-time distance computation among moving convex bodiesComputational Geometry: Theory and Applications, 15(1-3):51–68, 2000.
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R. Kindel, D. Hsu, J.C. Latombe, and S. Rock. Kinodynamic motion planning amidst moving obstacles. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 537–543, 2000.
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D. Hsu, R. Kindel, J.C. Latombe, and S. Rock. Control-based randomized motion planning for dynamic environments. In B.R. Donald and others, editors, Algorithmic and Computational Robotics: New Directions—Proc. Workshop on the Algorithmic Foundations of Robotics (WAFR), pp. 247–264, A. K. Peters, Wellesley, MA, 2000.
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D. Hsu. Randomized Single-query Motion Planning in Expansive Spaces. Ph.D. Thesis, Dept. of Computer Science, Stanford University, Stanford, CA, 2000.
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L.J. Guibas, D. Hsu, and L. Zhang. H-Walk: hierarchical distance computation for moving convex bodies. In Proc. ACM Symp. on Computational Geometry, pp. 265–273, 1999.
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D. Hsu, J.C. Latombe, and S. Sorkin. Placing a robot manipulator amid obstacles for optimized execution. In Proc. IEEE Int. Symp. on Assembly & Task Planning, pp. 280–285, 1999.
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D. Hsu, J.C. Latombe, and R. Motwani. Path planning in expansive configuration spacesInt. J. Computational Geometry & Applications, 9(4-5):495–512, 1999.
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D. Hsu, J.C. Latombe, R. Motwani, and L.E. Kavraki. Capturing the connectivity of high-dimensional geometric spaces by parallelizable random sampling techniques. In P.M. Pardalos and S. Rajasekaran, editors, Advances in randomized parallel computing, pp. 159–182, Kluwer Academic Publishers, Boston, MA, 1999.
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D. Hsu, L.E. Kavraki, J.C. Latombe, R. Motwani, and S. Sorkin. On finding narrow passages with probabilistic roadmap planners. In P.K. Agarwal and others, editors, Robotics: The Algorithmic Perspective—Proc. Workshop on the Algorithmic Foundations of Robotics (WAFR), pp. 141–154, A. K. Peters, Wellesley, MA, 1998.
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D. Hsu, J.C. Latombe, and R. Motwani. Path planning in expansive configuration spaces. In Proc. IEEE Int. Conf. on Robotics & Automation, pp. 2719–2726, 1997.
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H. Alt, D. Hsu, and J. Snoeyink. Computing the largest inscribed isothetic rectangle. In Proc. Canadian Conf. on Computational Geometry, pp. 67–72, 1995.
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