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Publications by Anastasiia Varava

Peer reviewed

Articles

[1]
Z. Weng et al., "Interactive Perception for Deformable Object Manipulation," IEEE Robotics and Automation Letters, vol. 9, no. 9, pp. 7763-7770, 2024.
[2]
M. Lippi et al., "Enabling Visual Action Planning for Object Manipulation Through Latent Space Roadmap," IEEE Transactions on robotics, vol. 39, no. 1, pp. 57-75, 2023.
[3]
A. A. Medbouhi et al., "InvMap and Witness Simplicial Variational Auto-Encoders," MACHINE LEARNING AND KNOWLEDGE EXTRACTION, vol. 5, no. 1, pp. 199-236, 2023.
[4]
O. Gustavsson et al., "Cloth manipulation based on category classification and landmark detection," International Journal of Advanced Robotic Systems, vol. 19, no. 4, 2022.
[5]
H. Song et al., "Herding by caging : a formation-based motion planning framework for guiding mobile agents," Autonomous Robots, vol. 45, no. 5, pp. 613-631, 2021.
[6]
H. Yin, A. Varava and D. Kragic, "Modeling, learning, perception, and control methods for deformable object manipulation," Science Robotics, vol. 6, no. 54, 2021.
[7]
M. C. Welle et al., "Partial caging : a clearance-based definition, datasets, and deep learning," Autonomous Robots, vol. 45, no. 5, pp. 647-664, 2021.
[8]
O. Kravchenko et al., "A Robotics-Inspired Screening Algorithm for Molecular Caging Prediction," Journal of Chemical Information and Modeling, vol. 60, no. 3, pp. 1302-1316, 2020.
[9]
I. Garcia-Camacho et al., "Benchmarking Bimanual Cloth Manipulation," IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 1111-1118, 2020.
[10]
A. Varava et al., "Free Space of Rigid Objects : Caging, Path Non-existence, and Narrow Passage Detection," Springer Proceedings in Advanced Robotics, vol. 14, pp. 19-35, 2020.
[11]
A. Varava et al., "Free space of rigid objects : caging, path non-existence, and narrow passage detection," The international journal of robotics research, 2020.
[12]
A. Varava, D. Kragic and F. T. Pokorny, "Caging Grasps of Rigid and Partially Deformable 3-D Objects With Double Fork and Neck Features," IEEE Transactions on robotics, vol. 32, no. 6, pp. 1479-1497, 2016.

Conference papers

[13]
G. L. Marchetti et al., "An Efficient and Continuous Voronoi Density Estimator," in Proceedings of the 26th International Conference on Artificial Intelligence and Statistics, AISTATS 2023, 2023, pp. 4732-4744.
[14]
G. L. Marchetti et al., "Equivariant Representation Learning via Class-Pose Decomposition," in Proceedings of the 26th International Conference on Artificial Intelligence and Statistics, AISTATS 2023, 2023, pp. 4745-4756.
[15]
A. Reichlin et al., "Learning Geometric Representations of Objects via Interaction," in Machine Learning and Knowledge Discovery in Databases: Research Track - European Conference, ECML PKDD 2023, Proceedings, 2023, pp. 629-644.
[16]
A. Kravchenko et al., "Active Nearest Neighbor Regression Through Delaunay Refinement," in Proceedings of the 39th International Conference on Machine Learning, 2022, pp. 11650-11664.
[17]
C. Chamzas et al., "Comparing Reconstruction- and Contrastive-based Models for Visual Task Planning," in 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2022, pp. 12550-12557.
[18]
P. Poklukar et al., "Delaunay Component Analysis for Evaluation of Data Representations," in Proceedings 10th International Conference on Learning Representations, ICLR 2022, 2022.
[19]
P. Tajvar et al., "Robust motion planning for non-holonomic robots with planar geometric constraints," in Robotics Research : The 19th International Symposium ISRR, 2022, pp. 850-866.
[20]
V. Polianskii et al., "Voronoi Density Estimator for High-Dimensional Data : Computation, Compactification and Convergence," in Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, 2022, pp. 1644-1653.
[21]
P. Poklukar, A. Varava and D. Kragic, "GeomCA : Geometric Evaluation of Data Representations," in International Conference On Machine Learning, Vol 139, 2021.
[22]
P. Poklukar, A. Varava and D. Kragic, "GeomCA: Geometric Evaluation of Data Representations," in Proceedings of Machine Learning Research : Proceedings of the 38th International Conference on Machine Learning, 2021, pp. 8588-8598.
[23]
Z. Weng et al., "Graph-based Task-specific Prediction Models for Interactions between Deformable and Rigid Objects," in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021, pp. 5741-5748.
[24]
G. L. Marchetti et al., "Learning Coarsened Dynamic Graph Representations for Deformable Object Manipulation," in 2021 20Th International Conference On Advanced Robotics (ICAR), 2021, pp. 955-960.
[25]
R. Antonova et al., "Sequential Topological Representations for Predictive Models of Deformable Objects," in Proceedings of the 3rd Conference on Learning for Dynamics and Control, L4DC 2021, 2021, pp. 348-360.
[26]
J. Karlsson et al., "When to Terminate : Path Non-existence Verification Improves Sampling-based Motion Planning," in 2021 20Th International Conference On Advanced Robotics (ICAR), 2021, pp. 594-600.
[27]
[28]
T. Ziegler et al., "Fashion Landmark Detection and Category Classification for Robotics," in Proceedings IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC 2020), 2020.
[29]
M. Lippi et al., "Latent Space Roadmap for Visual Action Planning of Deformable and Rigid Object Manipulation," in 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020, pp. 5619-5626.
[30]
A. Varava et al., "Partial Caging : A Clearance-Based Definition and Deep Learning," in IEEE International Conference on Intelligent Robots and Systems, 2019, pp. 1533-1540.
[31]
A. Varava et al., "Free Space of Rigid Objects: Caging, Path Non-Existence, and Narrow Passage Detection," in Workshop on Algorithmic Foundations of Robotics, 2018.
[32]
A. Varava et al., "Caging and Path Non-Existence: a Deterministic Sampling-Based Verification Algorithm," in International Symposium on Robotics Research, 2017.

Non-peer reviewed

Theses

[34]
A. Varava, "Path-Connectivity of the Free Space : Caging and Path Existence," Doctoral thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2019:30, 2019.
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2024-10-04 00:03:41