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Neha Das
Neha Das
Doctoral Candidate, Technical University of Munich
Verified email at tum.de - Homepage
Title
Cited by
Cited by
Year
Model-based inverse reinforcement learning from visual demonstrations
N Das, S Bechtle, T Davchev, D Jayaraman, A Rai, F Meier
Conference on Robot Learning, 1930-1942, 2021
672021
Learning state-dependent losses for inverse dynamics learning
K Morse, N Das, Y Lin, AS Wang, A Rai, F Meier
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems†…, 2020
82020
Beta dvbf: Learning state-space models for control from high dimensional observations
N Das, M Karl, P Becker-Ehmck, P van der Smagt
arXiv preprint arXiv:1911.00756, 2019
52019
Safe learning-based control of elastic joint robots via control barrier functions
A Lederer, A Begzadić, N Das, S Hirche
IFAC-PapersOnLine 56 (2), 2250-2256, 2023
42023
Learning extended body schemas from visual keypoints for object manipulation
S Bechtle, N Das, F Meier
arXiv preprint arXiv:2011.03882, 2020
42020
Online detection of compensatory strategies in human movement with supervised classification: a pilot study
N Das, S Endo, S Patel, C Krewer, S Hirche
Frontiers in Neurorobotics 17, 2023
22023
Multimodal learning of keypoint predictive models for visual object manipulation
S Bechtle, N Das, F Meier
IEEE Transactions on Robotics 39 (2), 1212-1224, 2023
12023
Assessing Human-Human Kinematics for the Implementation of Robot-Assisted Physical Therapy in Humanoids: A Pilot Study
S Nertinger, N Das, E Satoshi, A Naceri, S Hirche, S Haddadin
2023 International Conference on Rehabilitation Robotics (ICORR), 1-6, 2023
2023
Time Series Classification for Detecting Parkinson's Disease from Wrist Motions
C Doniť, N Das, S Endo, S Hirche
arXiv preprint arXiv:2304.11265, 2023
2023
Deep Learning based Uncertainty Decomposition for Real-time Control
N Das, J Umlauft, A Lederer, A Capone, T Beckers, S Hirche
IFAC-PapersOnLine 56 (2), 847-853, 2023
2023
Seminar Report: Deep Learning Sequence Modelling (Natural Language Processing)
N Das
Learning State-Dependent Losses for Inverse Dynamics Learning
N Das, K Morse, Y Lin, A Wang, A Rai, F Meier
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Articles 1–12