Publications


2018

[1]
L. H. Gilpin, J. C. Macbeth, and E. Florentine, “Monitoring Scene Understanders with Conceptual Primitive Decomposition and Commonsense Knowledge,” (Accepted) Advances in Cognitive Systems [Online]. Available: http://www.cogsys.org/papers/ACSvol6/article01.pdf

[2]
J. DeCastro, L. Liebenwein, C.-I. Vasile, R. Tedrake, S. Karaman, and D. Rus, “Counterexample-Guided Safety Contracts for Autonomous Driving,” in The 13th International Workshop on the Algorithmic Foundations of Robotics (WAFR 2018), 2018, p. 16.

[3]
J.-Y. Zhu, Z. Zhang, C. Zhang, J. Wu, A. Torralba, J. B. Tenenbaum, and W. T. Freeman, “Visual Object Networks: Natural Image Generation with Disentangled 3D Representation,” in NIPS 2018, 2018.

[4]
X. Zhang, Z. Zhang, C. Zhang, J. B. Tenenbaum, W. T. Freeman, and J. Wu, “On the Generalization of Single-View 3D Reconstruction Algorithms,” in NIPS 2018, 2018.

[5]
Yilun Du, Zhijian Liu, Hector Basevi, Ales Leonardis, William T Freeman, J. B. Tenenbaum, and J. Wu, “Learning to Exploit Stability for 3D Scene Parsing,” in NIPS 2018, 2018.

[6]
K. Yi, C. Gan, P. Kohli, A. Torralba, Joshua B. Tenenbaum, and J. Wu, “Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding,” in NIPS 2018, 2018.

[7]
S. Yao, T. M. H. Hsu, J.-Y. Zhu, J. Wu, A. Torralba, W. T. Freeman, and J. B. Tenenbaum, “3D-Aware Scene Manipulation via Inverse Graphics,” in NIPS 2018, 2018 [Online]. Available: http://arxiv.org/abs/1808.09351. [Accessed: 07-Sep-2018]

[8]
O. Bastani, Y. Pu, and A. Solar-Lezama, “Verifiable Reinforcement Learning via Policy Extraction,” in NIPS 2018; arXiv:1805.08328 [cs, stat], 2018 [Online]. Available: http://arxiv.org/abs/1805.08328. [Accessed: 26-Sep-2018]

[9]
A. M. Jasour, A. Hofmann, and B. C. Williams, “Moment-Sum-Of-Squares Approach for Fast Risk Estimation in Uncertain Environments,” in IEEE CDC 2018, 2018.

[10]
X. Huang, A. Jasour, M. Deyo, A. Hofmann, and B. C. Williams, “Hybrid Risk-Aware Conditional Planning with Applications in Autonomous Vehicles,” in IEEE CDC 2018, 2018.

[11]
S. Chou, F. Kjolstad, and S. Amarasinghe, “Format Abstraction for Sparse Tensor Algebra Compilers,” presented at the International Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA 2018), 2018, vol. 2, p. 30.

[12]
F. Naser, I. Gilitschenski, G. Rosman, A. Amini, F. Durand, A. Torralba, G. W. Wornell, W. T. Freeman, S. Karaman, and D. Rus, “ShadowCam: Real-Time Detection of Moving Obstacles Behind A Corner For Autonomous Vehicles,” in 21st IEEE International Conference on Intelligent Transportation Systems (ITSC 2018), 2018.

[13]
T.-M. Li, M. Aittala, F. Durand, and J. Lehtinen, “Differentiable Monte Carlo Ray Tracing through Edge Sampling,” in ACM Trans. Graph. (Proc. SIGGRAPH Asia), 2018, vol. 37, pp. 222:1–222:11.

[14]
L. H. Gilpin, D. Bau, B. Z. Yuan, A. Bajwa, M. Specter, and L. Kagal, “Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning,” in The 5th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2018), 2018 [Online]. Available: http://arxiv.org/abs/1806.00069

[15]
Y.-L. Kuo, A. Barbu, and B. Katz, “Deep sequential models for sampling-based planning,” in IROS 2018, 2018.

[16]
E. Donlon, S. Dong, M. Liu, J. Li, E. Adelson, and A. Rodriguez, “GelSlim: A High-Resolution, Compact, Robust, and Calibrated Tactile-sensing Finger,” in IROS 2018, 2018.

[17]
S. Dai, M. Orton, S. Schaffert, A. Hofmann, and B. Williams, “Improving Trajectory Optimization using a Roadmap Framework,” in IROS 2018, 2018.

[18]
A. Amini, W. Schwarting, G. Rosman, B. Araki, S. Karaman, and D. Rus, “Variational Autoencoder for End-to-End Control of Autonomous Driving with Novelty Detection and Training De-biasing,” in IROS 2018, 2018.

[19]
D. Harwath, A. Recasens, D. Surís, G. Chuang, A. Torralba, and J. Glass, “Jointly Discovering Visual Objects and Spoken Words from Raw Sensory Input,” in ECCV 2018, Cham, 2018, vol. 11210, pp. 659–677 [Online]. Available: https://doi.org/10.1007/978-3-030-01231-1_40

[20]
L. Liebenwein, C. Baykal, I. Gilitschenski, S. Karaman, and D. Rus, “Sampling-Based Approximation Algorithms for Reachability Analysis with Provable Guarantees,” in Robotics: Science and Systems, 2018 [Online]. Available: http://www.roboticsproceedings.org/rss14/p14.pdf

[21]
A. Zlateski, R. Jaroensri, P. Sharma, and F. Durand, “On the Importance of Label Quality for Semantic Segmentation,” in CVPR 2018, 2018 [Online]. Available: http://openaccess.thecvf.com/content_cvpr_2018/papers/Zlateski_On_the_Importance_CVPR_2018_paper.pdf

[22]
X. Sun, J. Wu, X. Zhang, Z. Zhang, C. Zhang, Tianfan Xue, Joshua B. Tenenbaum, and William T. Freeman, “Pix3D: Dataset and Methods for 3D Object Modeling from a Single Image,” in CVPR 2018, 2018 [Online]. Available: http://cvpr2018.thecvf.com/program/main_conference

[23]
W. Yuan, Y. Mo, S. Wang, and E. H. Adelson, “Active Clothing Material Perception using Tactile Sensing and Deep Learning,” in ICRA 2018 (accepted), 2018 [Online]. Available: https://ras.papercept.net/conferences/conferences/ICRA18/program/ICRA18_ContentListWeb_3.html#wep@o_08

[24]
A. Pierson, W. Schwarting, S. Karaman, and D. Rus, “Navigating Congested Environments with Risk Level Sets,” in ICRA 2018 (accepted), 2018 [Online]. Available: https://icra2018.org/program-2/

[25]
T. Ort, L. Paull, and D. Rus, “Autonomous Vehicle Navigation in Rural Environments without Detailed Prior Maps,” in ICRA 2018 (accepted), 2018 [Online]. Available: https://toyota.csail.mit.edu/sites/default/files/documents/papers/ICRA2018_AutonomousVehicleNavigationRuralEnvironment.pdf

[26]
J. Li, S. Dong, and E. Adelson, “Slip Detection with Combined Tactile and Visual Information,” in ICRA 2018 (accepted), 2018 [Online]. Available: https://ras.papercept.net/conferences/conferences/ICRA18/program/ICRA18_ContentListWeb_4.html#thp@u_03

[27]
J. Karlsson, C.-I. Vasile, J. Tumova, S. Karaman, and D. Rus, “Multi-vehicle motion planning for social optimal mobility-on-demand,” in ICRA 2018 (accepted), 2018 [Online]. Available: https://icra2018.org/program-2/

[28]
A. Amini, L. Paull, Thomas Balch, Sertac Karaman, and D. Rus, “Learning Steering Bounds for Parallel Autonomous Systems,” in ICRA 2018 (accepted), 2018 [Online]. Available: https://icra2018.org/program-2/

[29]
D. Harwath, G. Chuang, and J. Glass, “Vision as an Interlingua: Learning Multilingual Semantic Embeddings of Untranscribed Speech,” in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018, pp. 4969–4973 [Online]. Available: https://doi.org/10.1109/ICASSP.2018.8462396

[30]
L. H. Gilpin, C. Zaman, D. Olson, and B. Z. Yuan, “Reasonable Perception: Connecting Vision and Language Systems for Validating Scene Descriptions,” in The 2018 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’18), 2018, pp. 115–116 [Online]. Available: https://doi.org/10.1145/3173386.3176994

[31]
Z. Jia, A. Zlateski, F. Durand, and K. Li, “Optimizing N-Dimensional,Winograd-Based Convolution for Manycore CPUs,” in Principles and Practice of Parallel Programming 2018 (PPoPP 2018), Vösendorf / Wien, Austria, 2018 [Online]. Available: https://doi.org/10.1145/3178487.3178496

[32]
A. Zlateski, Z. Jia, K. Li, and F. Durand, “A Deeper Look at FFT and Winograd Convolutions,” in SysML Conference, Stanford, CA, 2018 [Online]. Available: http://www.sysml.cc/doc/28.pdf

[33]
Z. Jia, A. Zlateski, F. Durand, and K. Li, “Towards Optimal Winograd Convolution on Manycores,” in SysML Conference, Stanford, CA, 2018 [Online]. Available: http://www.sysml.cc/doc/47.pdf

[34]
L. Gilpin, “Reasonableness Monitors,” in The 23rd AAAI/SIGAI Doctoral Consortium (DC) at AAAI-18 (accepted), 2018 [Online]. Available: https://aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17361/16430



2017

[35]
K. Leidal, D. Harwath, and J. Glass, “Learning Modality-Invariant Representations for Speech and Images,” in 2017 IEEE Automatic Speech Recognition and Understanding Workshop, Okinawa, Japan, 2017 [Online]. Available: https://asru2017.org/Papers/ViewPapers.asp?PaperNum=1259

[36]
L. Wang and B. K. P. Horn, “Machine Vision to Alert Roadside Personnel of Night Traffic Threats,” IEEE Transactions on Intelligent Transportation Systems, Dec. 2017 [Online]. Available: https://doi.org/10.1109/TITS.2017.2772225

[37]
A. Amini, A. Soleimany, S. Karaman, and D. Rus, “Spatial Uncertainty Sampling for End to End Control,” in Bayesian Deep Learning, NIPS 2017 Workshop, Long Beach, CA, US, 2017 [Online]. Available: http://bayesiandeeplearning.org/2017/papers/25.pdf

[38]
Z. Zhang, Q. Li, Z. Huang, J. Wu, J. Tenenbaum, and B. Freeman, “Shape and Material from Sound,” in Advances in Neural Information Processing Systems 30, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, Eds. Curran Associates, Inc., 2017, pp. 1278–1288 [Online]. Available: http://papers.nips.cc/paper/6727-shape-and-material-from-sound.pdf

[39]
J. Wu, Y. Wang, T. Xue, X. Sun, B. Freeman, and J. Tenenbaum, “MarrNet: 3D Shape Reconstruction via 2.5D Sketches,” in Advances in Neural Information Processing Systems 30, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, Eds. Curran Associates, Inc., 2017, pp. 540–550 [Online]. Available: http://papers.nips.cc/paper/6657-marrnet-3d-shape-reconstruction-via-25d-sketches.pdf

[40]
J. Wu, E. Lu, P. Kohli, B. Freeman, and J. Tenenbaum, “Learning to See Physics via Visual De-animation,” in Advances in Neural Information Processing Systems 30, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, Eds. Curran Associates, Inc., 2017, pp. 152–163 [Online]. Available: http://papers.nips.cc/paper/6620-learning-to-see-physics-via-visual-de-animation.pdf

[41]
M. Tucker, A. Derya, R. Paul, G. Stein, and N. Roy, “Learning Unknown Groundings for Natural Language Interaction with Mobile Robots,” in International Symposium on Robotics Research 2017, Puerto Varas, Chile, 2017 [Online]. Available: https://parasol.tamu.edu/isrr/isrr2017/program.php

[42]
A. Pierson and D. Rus, “Distributed Target Tracking in Cluttered Environments with Guaranteed Collision Avoidance,” in The 1st International Symposium on Multi-Robot and Multi-Agent Systems, Los Angeles, CA, USA, 2017 [Online]. Available: https://mrs2017.org/schedule/

[43]
L. Liebenwein, W. Schwarting, C.-I. Vasile, J. DeCastro, J. Alonso-Mora, S. Karaman, and D. Rus, “Compositional and Contract-based Verification for Autonomous Driving on Road Networks,” in International Symposium on Robotics Research 2017, Puerto Varas, Chile, 2017 [Online]. Available: https://parasol.tamu.edu/isrr/isrr2017/program.php

[44]
M. Janner, J. Wu, T. D. Kulkarni, I. Yildirim, and J. Tenenbaum, “Self-Supervised Intrinsic Image Decomposition,” in Advances in Neural Information Processing Systems 30, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett, Eds. Curran Associates, Inc., 2017, pp. 5938–5948 [Online]. Available: http://papers.nips.cc/paper/7175-self-supervised-intrinsic-image-decomposition.pdf

[45]
G. Izatt, H. Dai, and R. Tedrake, “Globally Optimal Object Pose Estimation in Point Clouds with Mixed-Integer Programming,” in International Symposium on Robotics Research 2017, Puerto Varas, Chile, 2017 [Online]. Available: https://parasol.tamu.edu/isrr/isrr2017/program.php

[46]
B. K. P. Horn and L. Wang, “Wave Equation of Suppressed Traffic Flow Instabilities,” IEEE Transactions on Intelligent Transportation Systems, Dec. 2017 [Online]. Available: https://doi.org/10.1109/TITS.2017.2767595

[47]
H. Dai, G. Izatt, and R. Tedrake, “Global Inverse Kinematics via Mixed-Integer Convex Optimization,” in International Symposium on Robotics Research 2017, Puerto Varas, Chile, 2017 [Online]. Available: https://parasol.tamu.edu/isrr/isrr2017/program.php

[48]
N. Glabinski, R. Paul, and N. Roy, “Grounding Natural Language Instructions with Unknown Object References using Learned Visual Attributes,” in AAAI Fall Symposium on Natural Communication for Human-Robot Collaboration (NCHRC), 2017, 2017.

[49]
W. Yuan, S. Dong, and E. H. Adelson, “GelSight: High-Resolution Robot Tactile Sensors for Estimating Geometry and Force,” Sensors, vol. 17, no. 12, Nov. 2017 [Online]. Available: http://www.mdpi.com/1424-8220/17/12/2762

[50]
B. Wolfe, J. Dobres, R. Rosenholtz, and B. Reimer, “More than the Useful Field: Considering peripheral vision in driving,” Applied Ergonomics, vol. 65, pp. 316–325, Nov. 2017 [Online]. Available: https://doi.org/10.1016/j.apergo.2017.07.009

[51]
N. W. Kim, Z. Bylinskii, M. A. Borkin, K. Z. Gajos, A. Oliva, F. Durand, and H. Pfister, “BubbleView: a validation of a mouse-contingent interface for crowdsourcing image importance and tracking visual attention,” ACM Transactions on Computer-Human Interaction (TOCHI), vol. 24, no. 5, pp. 36:1-36:40, Nov. 2017 [Online]. Available: https://doi.org/10.1145/3131275

[52]
R. Calandra, A. Owens, M. Upadhyaya, W. Yuan, J. Lin, E. H. Adelson, and S. Levine, “The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?,” in 1st Conference on Robot Learning (CoRL 2017), Mountain View, United States., 2017 [Online]. Available: http://proceedings.mlr.press/v78/calandra17a/calandra17a.pdf

[53]
F. Kjolstad, S. Kamil, S. Chou, D. Lugato, and S. Amarasinghe, “The tensor algebra compiler,” Proceedings of the ACM on Programming Languages, vol. 1, no. OOPSLA, pp. 1–29, Oct. 2017 [Online]. Available: https://doi.org/10.1145/3133901

[54]
W. Schwarting, J. Alonso-Mora, L. Paull, S. Karaman, and D. Rus, “Safe Nonlinear Trajectory Generation for Parallel Autonomy with a Dynamic Vehicle Model,” IEEE Transactions on Intelligent Transportation Systems, Oct. 2017 [Online]. Available: https://doi.org/10.1109/TITS.2017.2771351

[55]
G. Rosman, L. Paull, and D. Rus, “Hybrid Control and Learning with Coresets for Autonomous Vehicles,” in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada, 2017 [Online]. Available: https://doi.org/10.1109/IROS.2017.8206612

[56]
S. Dong, W. Yuan, and E. Adelson, “Improved GelSight Tactile Sensor for Measuring Geometry and Slip,” in IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada, 2017 [Online]. Available: http://doi.org/10.1109/IROS.2017.8202149

[57]
L. Wang and B. K. Horn, “Time-to-Contact control for safety and reliability of self-driving cars,” in Smart Cities Conference (ISC2), 2017 International, 2017, pp. 1–4 [Online]. Available: https://doi.org/10.1109/ISC2.2017.8090789

[58]
R. Paul, A. Barbu, S. Felshin, B. Katz, and N. Roy, “Temporal Grounding Graphs for Language Understanding with Accrued Visual-Linguistic Context (Cross-Submission with IJCAI 2017),” in The 1st Workshop on Language Grounding for Robotics at ACL 2017, Vancouver, Canada, 2017 [Online]. Available: https://robonlp2017.github.io/schedule.html

[59]
R. Paul, A. Barbu, S. Felshin, B. Katz, and N. Roy, “Temporal Grounding Graphs for Language Understanding with Accrued Visual-Linguistic Context,” in International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, 2017 [Online]. Available: https://doi.org/10.24963/ijcai.2017/629

[60]
W. Yuan, S. Wang, S. Dong, and E. Adelson, “Connecting Look and Feel: Associating the visual and tactile properties of physical materials,” in 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA, 2017 [Online]. Available: https://doi.org/10.1109/CVPR.2017.478. [Accessed: 10-Jul-2017]

[61]
J. Wu, J. B. Tenenbaum, and P. Kohli, “Neural Scene De-Rendering,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, Honolulu, Hawaii, 2017 [Online]. Available: https://doi.org/10.1109/CVPR.2017.744

[62]
A. A. Soltani, H. Huang, J. Wu, T. D. Kulkarni, and J. B. Tenenbaum, “Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative Networks,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, Honolulu, Hawaii, 2017 [Online]. Available: https://doi.org/10.1109/CVPR.2017.269

[63]
D. Harwath and J. Glass, “Learning Word-Like Units from Joint Audio-Visual Analysis,” in The 55th Annual Meeting of the Association for Computational Linguistics, 2017, pp. 506–517 [Online]. Available: https://doi.org/10.18653/v1/P17-1047

[64]
M. Gharbi, J. Chen, J. Barron, S. Hasinoff, and F. Durand, “Deep Bilateral Learning for Real-Time Image Enhancement,” ACM Transactions on Graphics (TOG), vol. 36, no. 4, Jul. 2017 [Online]. Available: https://doi.org/10.1145/3072959.3073592

[65]
L. Anderson, T.-M. Li, J. Lehtinen, and F. Durand, “Aether: An Embedded Domain Specific Sampling Language for Monte Carlo Rendering,” ACM Transactions on Graphics (TOG), vol. 36, no. 4, Jul. 2017 [Online]. Available: https://doi.org/10.1145/3072959.3073704

[66]
W. Yuan, C. Zhu, A. Owens, M. A. Srinivasan, and E. H. Adelson, “Shape-independent Hardness Estimation Using Deep Learning and a GelSight Tactile Sensor,” in 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore, Singapore, 2017 [Online]. Available: https://doi.org/10.1109/ICRA.2017.7989116

[67]
C.-I. Vasile, J. Tumova, S. Karaman, C. Belta, and D. Rus, “Minimum-violation scLTL motion planning for mobility-on-demand,” in 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore, Singapore, 2017 [Online]. Available: https://doi.org/10.1109/ICRA.2017.7989177

[68]
W. Schwarting, J. Alonso-Mora, L. Paull, S. Karaman, and D. Rus, “Parallel Autonomy in Automated Vehicles: Safe Motion Generation with Minimal Intervention,” in 2017 IEEE International Conference on Robotics and Automation (ICRA), Singapore, Singapore, 2017 [Online]. Available: https://doi.org/10.1109/ICRA.2017.7989224

[69]
L. Paull, J. Tani, H. Ahn, J. Alonso-Mora, L. Carlone, M. Cáp, Y. F. Chen, C. Choi, J. Dusek, Y. Fang, D. Hoehener, S.-Y. Liu, M. Novitzky, I. F. Okuyama, J. Pazis, G. Rosman, V. Varricchio, H.-C. Wang, D. S. Yershov, H. Zhao, M. Benjamin, C. Carr, M. T. Zuber, S. Karaman, E. Frazzoli, D. D. Vecchio, D. Rus, J. P. How, J. J. Leonard, and A. Censi, “Duckietown: An open, inexpensive and flexible platform for autonomy education and research,” in 2017 IEEE International Conference on Robotics and Automation, ICRA 2017, Singapore, Singapore, 2017, pp. 1497–1504 [Online]. Available: https://doi.org/10.1109/ICRA.2017.7989179

[70]
B. Wolfe, L. Fridman, A. Kosovicheva, B. Seppelt, B. Mehler, R. Rosenholtz, and B. Reimer, “Perceiving the Roadway in the Blink of an Eye–Rapind Perception of the Road Environment and Prediction of Events,” in 9th International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design, Manchester Village, Vermont, 2017 [Online]. Available: http://drivingassessment.uiowa.edu/sites/default/files/DA2017/papers/33.pdf

[71]
F. Naser, D. Dorhout, S. Proulx, S. D. Pendleton, H. Andersen, W. Schwarting, L. Paull, J. Alonso-Mora, M. H. A. Jr., S. Karaman, R. Tedrake, J. Leonard, and D. Rus, “A Parallel Autonomy Research Platform,” in 2017 IEEE Intelligent Vehicles Symposium, 2017, pp. 933–940 [Online]. Available: https://doi.org/10.1109/IVS.2017.7995835

[72]
M. Monfort, M. Johnson, A. Oliva, and K. Hofmann, “Asynchronous Data Aggregation for Training End to End Visual Control Networks,” in Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, São Paulo, Brazil, 2017, pp. 530–537 [Online]. Available: http://dl.acm.org/citation.cfm?id=3091125.3091204

[73]
G. Izatt, G. Mirano, E. Adelson, and R. Tedrake, “Tracking objects with point clouds from vision and touch,” in Robotics and Automation (ICRA), 2017 IEEE International Conference on, 2017, pp. 4000–4007 [Online]. Available: https://doi.org/10.1109/ICRA.2017.7989460

[74]
Z. Bylinskii, T. Judd, A. Oliva, A. Torralba, and F. Durand, “What do different evaluation metrics tell us about saliency models?,” arxiv; submitted to IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Apr. 2017 [Online]. Available: https://arxiv.org/abs/1604.03605

[75]
L. H. Gilpin and B. Z. Yuan, “Getting Up to Speed on Vehicle Intelligence,” in 2017 AAAI Spring Symposium Series, Palo Alto, CA USA, 2017 [Online]. Available: https://aaai.org/ocs/index.php/SSS/SSS17/paper/view/15322/14599

[76]
L. Wang, B. K. P. Horn, and G. Strang, “Eigenvalue and Eigenvector Analysis of Stability for a Line of Traffic,” Studies in Applied Mathematics, vol. 138, no. 1, pp. 103–132, Jan. 2017 [Online]. Available: http://doi.wiley.com/10.1111/sapm.12144



2016

[77]
J. Wu, C. Zhang, T. Xue, W. T. Freeman, and J. Tenenbaum, “Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling,” in Advances in Neural Information Processing Systems 29, Barcelona, Spain, 2016, pp. 82–90 [Online]. Available: http://papers.nips.cc/paper/6096-learning-a-probabilistic-latent-space-of-object-shapes-via-3d-generative-adversarial-modeling.pdf

[78]
J. Wu, T. Xue, J. J. Lim, Y. Tian, J. B. Tenenbaum, A. Torralba, and W. T. Freeman, “Single Image 3D Interpreter Network,” in Computer Vision – ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VI, Cham, 2016, pp. 365–382 [Online]. Available: http://dx.doi.org/10.1007/978-3-319-46466-4_22

[79]
D. Harwath, A. Torralba, and J. Glass, “Unsupervised learning of spoken language with visual context,” in Advances in Neural Information Processing Systems, Barcelona, Spain, 2016 [Online]. Available: https://papers.nips.cc/paper/6186-unsupervised-learning-of-spoken-language-with-visual-context.pdf