A prototype autonomous agent for crew and equipment retrieval in space. - J. D. Erickson; D. E. Phinney; R. S. Norsworthy; Miriam Zacksenhouse; K. T. Hartness; T. T. Pham; L. F. Merkel; E. Y. Tu (IEA/AIE (2), 1989)

Characterization of one-dimensional texture-a point process approach. - Miriam Zacksenhouse; Gil Abramovich; Gad Hetsroni (ICASSP, 1998)

Segmenting Manipulative Hand Movements by Dividing Phase Plane Trajectorie. - Miriam Zacksenhouse; Thomas Moestl (ICRA, 1999)

Instantaneous model impedance control for robots. - Tomer Valency; Miriam Zacksenhouse (IROS, 2000)

Inherent structure of manipulative hand movements and its discriminative power. - Miriam Zacksenhouse; Paul Marcovici (IROS, 2000)

Sensitivity of basic oscillatory mechanisms for pattern generation and detection. - Miriam Zacksenhouse (Biol. Cybern., 2001)

Oscillatory neural networks for robotic yo-yo control. - Hui-Liang Jin; Miriam Zacksenhouse (IEEE Trans. Neural Networks, 2003)

Robotic yoyo playing with visual feedback. - Hui-Liang Jin; Miriam Zacksenhouse (IEEE Trans. Robotics, 2004)

An Info-Gap Approach to Linear Regression. - Miriam Zacksenhouse; Simona Nemets; Anna Yoffe; Yakov Ben-Haim; Mikhail A. Lebedev 001; Miguel A. L. Nicolelis (ICASSP (3), 2006)

Temporal Decoding by Phase-Locked Loops: Unique Features of Circuit-Level Implementations and Their Significance for Vibrissal Information Processing. - Miriam Zacksenhouse; Ehud Ahissar (Neural Comput., 2006)

Coordinative Structure of Manipulative Hand-Movements Facilitates Their Recognition. - Iris Dejmal; Miriam Zacksenhouse (IEEE Trans. Biomed. Eng., 2006)

Return Maps, Parameterization, and Cycle-Wise Planning of Yo-Yo Playing. - Hui-Liang Jin; Qian Ye; Miriam Zacksenhouse (IEEE Trans. Robotics, 2009)

Towards a biologically inspired open loop controller for dynamic biped locomotion. - Jonathan Spitz; Yizhar Or; Miriam Zacksenhouse (ROBIO, 2011)

Signal-independent timescale analysis (SITA) and its application for neural coding during reaching and walking. - Miriam Zacksenhouse; Mikhail A. Lebedev 001; Miguel A. L. Nicolelis (Frontiers Comput. Neurosci., 2014)

Humanoids can take Advantage of Crab-Walking Gaits. - Jonathan Spitz; Eric Sidorov; Miriam Zacksenhouse (Int. J. Humanoid Robotics, 2015)

Brain Responses to Errors During 3D Motion in a Hapto-Visual VR. - Boris Yazmir; Miriam Reiner; Hillel Pratt; Miriam Zacksenhouse (EuroHaptics (2), 2016)

Optimal feedback control framework suggests that changes in the preferred direction during BMI experiments may occur even with no adaptation. - Miri Benyamini; Miriam Zacksenhouse (SMC, 2016)

Attenuating Tremor Using Passive Devices. - Reuven Katz; Eran Buki; Miriam Zacksenhouse (AAATE Conf., 2017)

Vib-bracelet: a passive absorber for attenuating forearm tremor. - Eran Buki; Reuven Katz; Miriam Zacksenhouse; Ilana Schlesinger (Medical Biol. Eng. Comput., 2018)

Implementation of a Natural Dynamic Controller on an Under-actuated Compass-Biped Robot. - Ron Hartston; Rea Yakar; Reuven Katz; Miriam Zacksenhouse (IROS, 2019)

Neural Correlates of error processing during grasping with invasive brain-machine interfaces. - Miri Benyamini; Samuel R. Nason; Cynthia A. Chestek; Miriam Zacksenhouse (NER, 2019)

Deep Reinforcement Learning for Contact-Rich Skills Using Compliant Movement Primitives. - Oren Spector; Miriam Zacksenhouse (CoRR, 2020)

Learning Contact-Rich Assembly Skills Using Residual Admittance Policy. - Oren Spector; Miriam Zacksenhouse (IROS, 2021)

Reinforcement Learning of Impedance Policies for Peg-in-Hole Tasks: Role of Asymmetric Matrices. - Shir Kozlovsky; Elad Newman; Miriam Zacksenhouse (IEEE Robotics Autom. Lett., 2022)