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Mårten Björkman
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- affiliation: Royal Institute of Technology, Stockholm, Sweden
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2020 – today
- 2024
- [j17]Parag Khanna
, Jonathan Fredberg, Mårten Björkman
Hand It to Me Formally! Data-Driven Control for Human-Robot Handovers With Signal Temporal Logic. IEEE Robotics Autom. Lett. 9(10): 9039-9046 (2024) - [c61]Wenjie Yin, Yi Yu, Hang Yin
Scalable Motion Style Transfer with Constrained Diffusion Generation. AAAI 2024: 10234-10242 - [c60]Marcel Büsching, Josef Bengtson, David Nilsson, Mårten Björkman:
FlowIBR: Leveraging Pre-Training for Efficient Neural Image-Based Rendering of Dynamic Scenes. CVPR Workshops 2024: 8016-8026 - [c59]Yuchong Zhang
Will You Participate? Exploring the Potential of Robotics Competitions on Human-Centric Topics. HCI (2) 2024: 240-255 - [i40]Yuchong Zhang, Nona Rajabi, Farzaneh Taleb, Andrii Matviienko, Yong Ma, Mårten Björkman, Danica Kragic:
Mind Meets Robots: A Review of EEG-Based Brain-Robot Interaction Systems. CoRR abs/2403.06186 (2024) - [i39]Wenjie Yin, Xuejiao Zhao, Yi Yu, Hang Yin, Danica Kragic, Mårten Björkman:
LM2D: Lyrics- and Music-Driven Dance Synthesis. CoRR abs/2403.09407 (2024) - [i38]Yuchong Zhang, Miguel Vasco, Mårten Björkman, Danica Kragic:
Will You Participate? Exploring the Potential of Robotics Competitions on Human-centric Topics. CoRR abs/2403.18616 (2024) - [i37]Xiaomeng Zhu, Talha Bilal, Pär Mårtensson, Lars Hanson, Mårten Björkman, Atsuto Maki:
Towards Sim-to-Real Industrial Parts Classification with Synthetic Dataset. CoRR abs/2404.08778 (2024) - [i36]Jonathan Styrud, Matteo Iovino, Mikael Norrlöf, Mårten Björkman, Christian Smith:
Automatic Behavior Tree Expansion with LLMs for Robotic Manipulation. CoRR abs/2409.13356 (2024) - [i35]Alfredo Reichlin, Gustaf Tegnér, Miguel Vasco, Hang Yin, Mårten Björkman, Danica Kragic:
Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks. CoRR abs/2410.01476 (2024) - 2023
- [j16]Temitayo A. Olugbade
Human Movement Datasets: An Interdisciplinary Scoping Review. ACM Comput. Surv. 55(6): 126:1-126:29 (2023) - [j15]Wenjie Yin, Hang Yin
Multimodal dance style transfer. Mach. Vis. Appl. 34(4): 48 (2023) - [j14]Matteo Gamba, Erik Englesson, Mårten Björkman, Hossein Azizpour:
Deep Double Descent via Smooth Interpolation. Trans. Mach. Learn. Res. 2023 (2023) - [c58]Reza Dadfar, Sanaz Sabzevari, Mårten Björkman, Danica Kragic:
TD-GEM: Text-Driven Garment Editing Mapper. BMVC 2023: 787-788 - [c57]Matteo Gamba, Hossein Azizpour, Mårten Björkman:
On the Lipschitz Constant of Deep Networks and Double Descent. BMVC 2023: 871-880 - [c56]Xiaomeng Zhu
Towards Sim-to-Real Industrial Parts Classification with Synthetic Dataset. CVPR Workshops 2023: 4454-4463 - [c55]Parag Khanna
How do Humans take an Object from a Robot: Behavior changes observed in a User Study. HAI 2023: 372-374 - [c54]Nona Rajabi, Charles Chernik
Mental Face Image Retrieval Based on a Closed-Loop Brain-Computer Interface. HCI (9) 2023: 26-45 - [c53]Shuangshuang Chen
Learning Continuous Normalizing Flows For Faster Convergence To Target Distribution via Ascent Regularizations. ICLR 2023 - [c52]Jia Fu
Component attention network for multimodal dance improvisation recognition. ICMI 2023: 114-118 - [c51]Tanay Rastogi, Mårten Björkman:
Automated Construction of Time-Space Diagrams for Traffic Analysis Using Street-View Video Sequences. ITSC 2023: 2282-2288 - [c50]Nona Rajabi, Parag Khanna
Detecting the Intention of Object Handover in Human-Robot Collaborations: An EEG Study. RO-MAN 2023: 549-555 - [c49]Wenjie Yin, Ruibo Tu, Hang Yin, Danica Kragic, Hedvig Kjellström
Controllable Motion Synthesis and Reconstruction with Autoregressive Diffusion Models. RO-MAN 2023: 1102-1108 - [c48]Parag Khanna
Effects of Explanation Strategies to Resolve Failures in Human-Robot Collaboration. RO-MAN 2023: 1829-1836 - [c47]Parag Khanna
A Multimodal Data Set of Human Handovers with Design Implications for Human-Robot Handovers. RO-MAN 2023: 1843-1850 - [c46]Fangkai Yang
Diffusion-Based Time Series Data Imputation for Cloud Failure Prediction at Microsoft 365. ESEC/SIGSOFT FSE 2023: 2050-2055 - [c45]Sanaz Sabzevari, Ali Ghadirzadeh, Mårten Björkman, Danica Kragic:
PG-3DVTON: Pose-Guided 3D Virtual Try-on Network. VISIGRAPP (4: VISAPP) 2023: 819-829 - [c44]Wenjie Yin, Hang Yin, Kim Baraka
Dance Style Transfer with Cross-modal Transformer. WACV 2023: 5047-5056 - [i34]Matteo Gamba, Hossein Azizpour, Mårten Björkman:
On the Lipschitz Constant of Deep Networks and Double Descent. CoRR abs/2301.12309 (2023) - [i33]Parag Khanna, Mårten Björkman, Christian Smith:
Data-driven Grip Force Variation in Robot-Human Handovers. CoRR abs/2303.16009 (2023) - [i32]Parag Khanna, Elmira Yadollahi, Mårten Björkman, Iolanda Leite
User Study Exploring the Role of Explanation of Failures by Robots in Human Robot Collaboration Tasks. CoRR abs/2303.16010 (2023) - [i31]Parag Khanna, Mårten Björkman, Christian Smith:
A Multimodal Data Set of Human Handovers with Design Implications for Human-Robot Handovers. CoRR abs/2304.02154 (2023) - [i30]Wenjie Yin, Ruibo Tu, Hang Yin, Danica Kragic, Hedvig Kjellström, Mårten Björkman:
Controllable Motion Synthesis and Reconstruction with Autoregressive Diffusion Models. CoRR abs/2304.04681 (2023) - [i29]Reza Dadfar, Sanaz Sabzevari, Mårten Björkman, Danica Kragic:
TD-GEM: Text-Driven Garment Editing Mapper. CoRR abs/2305.18120 (2023) - [i28]Tanay Rastogi, Mårten Björkman:
Automated Construction of Time-Space Diagrams for Traffic Analysis Using Street-View Video Sequence. CoRR abs/2308.06098 (2023) - [i27]Fangkai Yang, Wenjie Yin, Lu Wang, Tianci Li, Pu Zhao, Bo Liu, Paul Wang, Bo Qiao, Yudong Liu, Mårten Björkman, Saravan Rajmohan, Qingwei Lin, Dongmei Zhang:
Diffusion-based Time Series Data Imputation for Microsoft 365. CoRR abs/2309.02564 (2023) - [i26]Marcel Büsching, Josef Bengtson, David Nilsson, Mårten Björkman:
FlowIBR: Leveraging Pre-Training for Efficient Neural Image-Based Rendering of Dynamic Scenes. CoRR abs/2309.05418 (2023) - [i25]Parag Khanna, Elmira Yadollahi, Mårten Björkman, Iolanda Leite
Effects of Explanation Strategies to Resolve Failures in Human-Robot Collaboration. CoRR abs/2309.10127 (2023) - [i24]Wenjie Yin, Qingyuan Yao, Yi Yu, Hang Yin, Danica Kragic, Mårten Björkman:
Music- and Lyrics-driven Dance Synthesis. CoRR abs/2310.00455 (2023) - [i23]Jia Fu, Jiarui Tan, Wenjie Yin, Sepideh Pashami, Mårten Björkman:
Component attention network for multimodal dance improvisation recognition. CoRR abs/2310.05938 (2023) - [i22]Wenjie Yin, Yi Yu, Hang Yin, Danica Kragic, Mårten Björkman:
Scalable Motion Style Transfer with Constrained Diffusion Generation. CoRR abs/2312.07311 (2023) - 2022
- [j13]Ali Ghadirzadeh, Petra Poklukar, Karol Arndt, Chelsea Finn, Ville Kyrki, Danica Kragic, Mårten Björkman:
Training and Evaluation of Deep Policies Using Reinforcement Learning and Generative Models. J. Mach. Learn. Res. 23: 174:1-174:37 (2022) - [j12]Atsuto Maki, Danica Kragic, Hedvig Kjellström
In Memoriam: Jan-Olof Eklundh. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 4488-4489 (2022) - [c43]Matteo Gamba, Adrian Chmielewski-Anders, Josephine Sullivan, Hossein Azizpour, Mårten Björkman:
Are All Linear Regions Created Equal? AISTATS 2022: 6573-6590 - [c42]Jón R. Baldvinsson, Milad Ganjalizadeh, Abdulrahman Alabbasi, Mårten Björkman, Amir Hossein Payberah:
IL-GAN: Rare Sample Generation via Incremental Learning in GANs. GLOBECOM 2022: 621-626 - [c41]Sumeyra Demir Kanik
Improving EEG-based Motor Execution Classification for Robot Control. HCI (14) 2022: 65-82 - [c40]Parag Khanna
Human Inspired Grip-Release Technique for Robot-Human Handovers. Humanoids 2022: 694-701 - [c39]Jonathan Styrud, Matteo Iovino, Mikael Norrlöf, Mårten Björkman, Christian Smith:
Combining Planning and Learning of Behavior Trees for Robotic Assembly. ICRA 2022: 11511-11517 - [i21]Matteo Gamba, Adrian Chmielewski-Anders, Josephine Sullivan, Hossein Azizpour, Mårten Björkman:
Are All Linear Regions Created Equal? CoRR abs/2202.11749 (2022) - [i20]Ali Ghadirzadeh, Petra Poklukar, Karol Arndt, Chelsea Finn, Ville Kyrki, Danica Kragic, Mårten Björkman:
Training and Evaluation of Deep Policies using Reinforcement Learning and Generative Models. CoRR abs/2204.08573 (2022) - [i19]Gustaf Tegnér
On the Subspace Structure of Gradient-Based Meta-Learning. CoRR abs/2207.03804 (2022) - [i18]Wenjie Yin, Hang Yin, Kim Baraka, Danica Kragic, Mårten Björkman:
Dance Style Transfer with Cross-modal Transformer. CoRR abs/2208.09406 (2022) - [i17]Matteo Gamba, Erik Englesson, Mårten Björkman, Hossein Azizpour:
Deep Double Descent via Smooth Interpolation. CoRR abs/2209.10080 (2022) - 2021
- [j11]Artur Czeszumski
Coordinating With a Robot Partner Affects Neural Processing Related to Action Monitoring. Frontiers Neurorobotics 15: 686010 (2021) - [j10]Ali Ghadirzadeh
Human-Centered Collaborative Robots With Deep Reinforcement Learning. IEEE Robotics Autom. Lett. 6(2): 566-571 (2021) - [c38]Shuangshuang Chen
Monte Carlo Filtering Objectives. IJCAI 2021: 2256-2262 - [c37]Ali Ghadirzadeh, Xi Chen, Petra Poklukar, Chelsea Finn
Bayesian Meta-Learning for Few-Shot Policy Adaptation Across Robotic Platforms. IROS 2021: 1274-1280 - [c36]Wenjie Yin, Hang Yin, Danica Kragic, Mårten Björkman:
Graph-based Normalizing Flow for Human Motion Generation and Reconstruction. RO-MAN 2021: 641-648 - [c35]Magnus Tarle
A World Model Based Reinforcement Learning Architecture for Autonomous Power System Control. SmartGridComm 2021: 364-370 - [i16]Ali Ghadirzadeh, Xi Chen, Petra Poklukar, Chelsea Finn, Mårten Björkman, Danica Kragic:
Bayesian Meta-Learning for Few-Shot Policy Adaptation Across Robotic Platforms. CoRR abs/2103.03697 (2021) - [i15]Jonathan Styrud, Matteo Iovino, Mikael Norrlöf, Mårten Björkman, Christian Smith:
Combining Planning and Learning of Behavior Trees for Robotic Assembly. CoRR abs/2103.09036 (2021) - [i14]Wenjie Yin, Hang Yin, Danica Kragic, Mårten Björkman:
Graph-based Normalizing Flow for Human Motion Generation and Reconstruction. CoRR abs/2104.03020 (2021) - [i13]Shuangshuang Chen, Sihao Ding, Yiannis Karayiannidis, Mårten Björkman:
Monte Carlo Filtering Objectives: A New Family of Variational Objectives to Learn Generative Model and Neural Adaptive Proposal for Time Series. CoRR abs/2105.09801 (2021) - [i12]M. M. N. Bienkiewicz, A. Smykovskyi, Temitayo A. Olugbade, S. Janaqi, Antonio Camurri, Nadia Bianchi-Berthouze, Mårten Björkman, Benoît G. Bardy:
Bridging the gap between emotion and joint action. CoRR abs/2108.06264 (2021) - 2020
- [j9]Judith Bütepage, Ali Ghadirzadeh, Özge Öztimur Karadag, Mårten Björkman, Danica Kragic:
Imitating by Generating: Deep Generative Models for Imitation of Interactive Tasks. Frontiers Robotics AI 7: 47 (2020) - [j8]Gabriela Zarzar Gandler, Carl Henrik Ek, Mårten Björkman, Rustam Stolkin, Yasemin Bekiroglu:
Object shape estimation and modeling, based on sparse Gaussian process implicit surfaces, combining visual data and tactile exploration. Robotics Auton. Syst. 126: 103433 (2020) - [c34]Fangkai Yang, Wenjie Yin, Tetsunari Inamura, Mårten Björkman, Christopher E. Peters:
Group Behavior Recognition Using Attention- and Graph-Based Neural Networks. ECAI 2020: 1626-1633 - [c33]Xi Chen, Ali Ghadirzadeh, Mårten Björkman, Patric Jensfelt:
Adversarial Feature Training for Generalizable Robotic Visuomotor Control. ICRA 2020: 1142-1148 - [c32]Shuangshuang Chen
Amortized Variational Inference for Road Friction Estimation. IV 2020: 1777-1784 - [c31]Fangkai Yang, Wenjie Yin, Mårten Björkman, Christopher Peters:
Impact of Trajectory Generation Methods on Viewer Perception of Robot Approaching Group Behaviors. RO-MAN 2020: 509-516 - [i11]Matteo Gamba, Stefan Carlsson, Hossein Azizpour, Mårten Björkman:
Hyperplane Arrangements of Trained ConvNets Are Biased. CoRR abs/2003.07797 (2020) - [i10]Ali Ghadirzadeh, Xi Chen, Wenjie Yin, Zhengrong Yi, Mårten Björkman, Danica Kragic:
Human-centered collaborative robots with deep reinforcement learning. CoRR abs/2007.01009 (2020) - [i9]Ali Ghadirzadeh, Petra Poklukar, Ville Kyrki, Danica Kragic, Mårten Björkman:
Data-efficient visuomotor policy training using reinforcement learning and generative models. CoRR abs/2007.13134 (2020)
2010 – 2019
- 2019
- [c30]Elena Sibirtseva, Ali Ghadirzadeh, Iolanda Leite
Exploring Temporal Dependencies in Multimodal Referring Expressions with Mixed Reality. HCI (10) 2019: 108-123 - [c29]Matteo Gamba, Hossein Azizpour, Stefan Carlsson, Mårten Björkman:
On the Geometry of Rectifier Convolutional Neural Networks. ICCV Workshops 2019: 793-797 - [c28]Xi Chen, Ali Ghadirzadeh, Mårten Björkman, Patric Jensfelt:
Meta-Learning for Multi-objective Reinforcement Learning. IROS 2019: 977-983 - [i8]Elena Sibirtseva, Ali Ghadirzadeh, Iolanda Leite, Mårten Björkman, Danica Kragic:
Exploring Temporal Dependencies in Multimodal Referring Expressions with Mixed Reality. CoRR abs/1902.01117 (2019) - [i7]Xi Chen, Ali Ghadirzadeh, Mårten Björkman, Patric Jensfelt:
Adversarial Feature Training for Generalizable Robotic Visuomotor Control. CoRR abs/1909.07745 (2019) - [i6]Judith Bütepage, Ali Ghadirzadeh, Özge Öztimur Karadag, Mårten Björkman, Danica Kragic:
Imitating by generating: deep generative models for imitation of interactive tasks. CoRR abs/1910.06031 (2019) - 2018
- [c27]Xi Chen, Ali Ghadirzadeh, John Folkesson
Deep Reinforcement Learning to Acquire Navigation Skills for Wheel-Legged Robots in Complex Environments. IROS 2018: 3110-3116 - [i5]Xi Chen, Ali Ghadirzadeh, Mårten Björkman, Patric Jensfelt:
Meta-Learning for Multi-objective Reinforcement Learning. CoRR abs/1811.03376 (2018) - 2017
- [c26]Ali Ghadirzadeh, Atsuto Maki, Danica Kragic, Mårten Björkman:
Deep predictive policy training using reinforcement learning. IROS 2017: 2351-2358 - [i4]Ali Ghadirzadeh, Atsuto Maki, Danica Kragic, Mårten Björkman:
Deep Predictive Policy Training using Reinforcement Learning. CoRR abs/1703.00727 (2017) - 2016
- [j7]Virgile Hogman, Mårten Björkman, Atsuto Maki, Danica Kragic:
A Sensorimotor Learning Framework for Object Categorization. IEEE Trans. Cogn. Dev. Syst. 8(1): 15-25 (2016) - [c25]Ali Ghadirzadeh, Judith Bütepage, Danica Kragic, Mårten Björkman:
Self-learning and adaptation in a sensorimotor framework. ICRA 2016: 551-558 - [c24]Ali Ghadirzadeh, Judith Bütepage, Atsuto Maki, Danica Kragic, Mårten Björkman:
A sensorimotor reinforcement learning framework for physical Human-Robot Interaction. IROS 2016: 2682-2688 - [i3]Ali Ghadirzadeh, Judith Bütepage, Danica Kragic, Mårten Björkman:
Self-learning and adaptation in a sensorimotor framework. CoRR abs/1601.00852 (2016) - [i2]Alessandro Pieropan, Mårten Björkman, Niklas Bergström, Danica Kragic:
Feature Descriptors for Tracking by Detection: a Benchmark. CoRR abs/1607.06178 (2016) - [i1]Ali Ghadirzadeh, Judith Bütepage, Atsuto Maki, Danica Kragic, Mårten Björkman:
A Sensorimotor Reinforcement Learning Framework for Physical Human-Robot Interaction. CoRR abs/1607.07939 (2016) - 2015
- [c23]Ali Ghadirzadeh, Atsuto Maki, Mårten Björkman:
A sensorimotor approach for self-learning of hand-eye coordination. IROS 2015: 4969-4975 - 2014
- [j6]Mårten Björkman, Niklas Bergström, Danica Kragic:
Detecting, segmenting and tracking unknown objects using multi-label MRF inference. Comput. Vis. Image Underst. 118: 111-127 (2014) - [c22]Ivan Lundberg, Mårten Björkman, Petter Ögren:
Intrinsic camera and hand-eye calibration for a robot vision system using a point marker. Humanoids 2014: 59-66 - [c21]Mårten Björkman, Yasemin Bekiroglu
Learning to disambiguate object hypotheses through self-exploration. Humanoids 2014: 560-565 - [c20]Ali Ghadirzadeh, Gert Kootstra
Learning visual forward models to compensate for self-induced image motion. RO-MAN 2014: 1110-1115 - 2013
- [c19]Virgile Hogman, Mårten Björkman, Danica Kragic:
Interactive object classification using sensorimotor contingencies. IROS 2013: 2799-2805 - [c18]Mårten Björkman, Yasemin Bekiroglu
Enhancing visual perception of shape through tactile glances. IROS 2013: 3180-3186 - 2012
- [c17]Lazaros Nalpantidis
YES - YEt another object segmentation: Exploiting camera movement. IROS 2012: 2116-2121 - 2011
- [c16]Niklas Bergström, Carl Henrik Ek, Mårten Björkman, Danica Kragic:
Scene Understanding through Autonomous Interactive Perception. ICVS 2011: 153-162 - [c15]Niklas Bergström, Mårten Björkman, Danica Kragic:
Generating object hypotheses in natural scenes through human-robot interaction. IROS 2011: 827-833 - 2010
- [j5]Babak Rasolzadeh, Mårten Björkman, Kai Huebner, Danica Kragic:
An Active Vision System for Detecting, Fixating and Manipulating Objects in the Real World. Int. J. Robotics Res. 29(2-3): 133-154 (2010) - [c14]Mårten Björkman, Danica Kragic:
Active 3D Segmentation through Fixation of Previously Unseen Objects. BMVC 2010: 1-11 - [c13]Mårten Björkman, Danica Kragic:
Active 3D scene segmentation and detection of unknown objects. ICRA 2010: 3114-3120 - [c12]Matthew Johnson-Roberson, Jeannette Bohg
Attention-based active 3D point cloud segmentation. IROS 2010: 1165-1170 - [c11]Jeannette Bohg
Strategies for multi-modal scene exploration. IROS 2010: 4509-4515
2000 – 2009
- 2008
- [c10]Kai Huebner, Mårten Björkman, Babak Rasolzadeh, Martina Schmidt, Danica Kragic:
Integration of Visual and Shape Attributes for Object Action Complexes. ICVS 2008: 13-22 - 2006
- [j4]Mårten Björkman, Jan-Olof Eklundh:
Vision in the real world: Finding, attending and recognizing objects. Int. J. Imaging Syst. Technol. 16(5): 189-208 (2006) - [c9]Patric Jensfelt, Danica Kragic, John Folkesson
A Framework for Vision Based bearing only 3D SLAM. ICRA 2006: 1944-1950 - [c8]Danica Kragic, Mårten Björkman:
Strategies for Object Manipulation using Foveal and Peripheral Vision. ICVS 2006: 50 - 2005
- [j3]Danica Kragic, Mårten Björkman, Henrik I. Christensen
Vision for robotic object manipulation in domestic settings. Robotics Auton. Syst. 52(1): 85-100 (2005) - [c7]Mårten Björkman, Jan-Olof Eklundh:
Foveated Figure-Ground Segmentation and Its Role in Recognition. BMVC 2005 - 2004
- [c6]Mårten Björkman, Jan-Olof Eklundh:
Attending, Foveating and Recognizing Objects in Real World Scenes. BMVC 2004: 1-10 - [c5]Mårten Björkman, Danica Kragic:
Combination of Foveal and Peripheral Vision for Object Recognition and Pose Estimation. ICRA 2004: 5135-5140 - 2002
- [j2]Mårten Björkman, Jan-Olof Eklundh:
Real-Time Epipolar Geometry Estimation of Binocular Stereo Heads. IEEE Trans. Pattern Anal. Mach. Intell. 24(3): 425-432 (2002) - 2001
- [c4]Mårten Björkman, Jan-Olof Eklundh:
Visual Cues for a Fixating Active Agent. RobVis 2001: 1-8 - 2000
- [c3]Mårten Björkman, Jan-Olof Eklundh:
A Real-Time System for Epipolar Geometry and Ego-Motion Estimation. CVPR 2000: 2506-2513
1990 – 1999
- 1999
- [c2]Mårten Björkman, Jan-Olof Eklundh:
Real-Time Epipolar Geometry Estimation and Disparity. ICCV 1999: 234-241 - 1997
- [j1]Fredrik Dahlgren, Per Stenström, Mårten Björkman:
Reducing the Read-Miss Penalty for Flat COMA Protocols. Comput. J. 40(4): 208-219 (1997) - 1995
- [c1]Mårten Björkman, Fredrik Dahlgren, Per Stenström:
Using hints to reduce the read miss penalty for flat COMA protocols. HICSS (1) 1995: 242-251
Coauthor Index
[c61] [c59] [i40] [i39] [i38] [i35] [j15] [c58] [c54] [c50] [c49] [c45] [c44] [i30] [i29] [i24] [i22] [j13] [j12] [c41] [i20] [i19] [i18] [j11] [j10] [c37] [c36] [i16] [i14] [j9] [i10] [i9] [c30] [i8] [i6] [c26] [i4] [j7] [c25] [c24] [i3] [i2] [i1] [j6] [c19] [c18] [c17] [c16] [c15] [j5] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [j3] [c5]
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