CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts | Paper Citation Record

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Unresolved cited work

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Reference 2

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Observation 0ef31ad5-7a25-4a95-99aa-68d1f2df0027 · outbound

This paper cites Featherstone,Rigid Body Dynamics Algorithms, ser.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Featherstone,Rigid Body Dynamics Algorithms, ser

Reference 3

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Observation f84122fb-1212-4bd8-b6d2-cdd898c8a35e · outbound

This paper cites Agile Maneuvers in Legged Robots: a Predictive Control Approach.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Agile Maneuvers in Legged Robots: a Predictive Control Approach

Reference 4

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Unresolved cited work

Reference 5

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Observation 829b750f-408c-4c7a-8f4a-9761ad2aaf69 · outbound

This paper cites Whole-body motion planning with centroidal dynamics and full kinematics,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Whole-body motion planning with centroidal dynamics and full kinematics,

Reference 6

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Observation d982a676-4b7a-4fb9-8a16-f4e43e7cc1b7 · outbound

This paper cites Momentum-aware trajectory optimisation using full-centroidal dynam- ics and implicit inverse kinematics,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Momentum-aware trajectory optimisation using full-centroidal dynam- ics and implicit inverse kinematics,

Reference 7

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This paper cites Wieber,Holonomy and Nonholonomy in the Dynamics of Articu- lated Motion.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Wieber,Holonomy and Nonholonomy in the Dynamics of Articu- lated Motion

Reference 8

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This paper cites Training and tracking in robotics.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Training and tracking in robotics

Reference 9

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This paper cites Model predictive control for micro aerial vehicles: A survey,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Model predictive control for micro aerial vehicles: A survey,

Reference 10

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This paper cites Tedrake,Underactuated Robotics, 2023.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Tedrake,Underactuated Robotics, 2023

Reference 11

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Observation 251c09e4-428f-4fa5-92bb-163c3a93df26 · outbound

This paper cites A review of learning- based dynamics models for robotic manipulation,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts A review of learning- based dynamics models for robotic manipulation,

Reference 12

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Observation 36c97f4d-4521-4df8-a7d7-a2745639460b · outbound

This paper cites A Survey on Imitation Learning for Contact-Rich Tasks in Robotics.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts A Survey on Imitation Learning for Contact-Rich Tasks in Robotics

Reference 13

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This paper cites Learning-based legged locomotion: State of the art and future perspectives,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Learning-based legged locomotion: State of the art and future perspectives,

Reference 14

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Observation 3f725a53-edc4-47ab-b46f-d94defac946e · outbound

This paper cites Physics-informed neural networks to model and control robots: A theoretical and experimental investigation,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Physics-informed neural networks to model and control robots: A theoretical and experimental investigation,

Reference 15

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This paper cites World models,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts World models,

Reference 16

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Unresolved cited work

Reference 17

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Observation 18006a6e-3f60-4329-8972-1c6e5fccadb0 · outbound

This paper cites Model-based Reinforcement Learning: A Survey.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Model-based Reinforcement Learning: A Survey

Reference 18

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Observation c6576ea2-7848-4e9d-8708-3d2204b1e08a · outbound

This paper cites Dream to Control: Learning Behaviors by Latent Imagination.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Dream to Control: Learning Behaviors by Latent Imagination

Reference 19

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Observation 2ceb78c8-3306-46a2-80e4-a950bdf8ae59 · outbound

This paper cites Deep learning in robotics: Survey on model structures and training strategies,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Deep learning in robotics: Survey on model structures and training strategies,

Reference 20

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Observation 0d15b71c-4f2a-42e9-8684-8ef0ab68136d · outbound

This paper cites Physics-informed machine learning,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Physics-informed machine learning,

Reference 21

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Observation 7ed91fe8-2264-44a1-bd0e-ae14114b7906 · outbound

This paper cites Physics-Informed Neural Operator for Learning Partial Differential Equations.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Physics-Informed Neural Operator for Learning Partial Differential Equations

Reference 22

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Observation 0f68e131-3f77-42d1-9f34-61275822a3c1 · outbound

This paper cites Lagrangian Neural Networks.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Lagrangian Neural Networks

Reference 23

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This paper cites Hamiltonian neural net- works,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Hamiltonian neural net- works,

Reference 24

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Observation d9b66573-3543-4dce-a037-2f7d37d7ad5c · outbound

This paper cites Stable port-hamiltonian neural networks,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Stable port-hamiltonian neural networks,

Reference 25

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This paper cites Sympnets: Intrinsic structure-preserving symplectic networks for identifying hamil- tonian systems,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Sympnets: Intrinsic structure-preserving symplectic networks for identifying hamil- tonian systems,

Reference 26

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This paper cites Td-mpc2: Scalable, robust world models for continuous control,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Td-mpc2: Scalable, robust world models for continuous control,

Reference 27

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This paper cites van der Schaft,L2-Gain and Passivity Techniques in Nonlinear Control, 3rd ed.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts van der Schaft,L2-Gain and Passivity Techniques in Nonlinear Control, 3rd ed

Reference 28

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This paper cites A review on safe reinforcement learning using lyapunov and barrier functions,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts A review on safe reinforcement learning using lyapunov and barrier functions,

Reference 29

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Observation dba8fd96-2a41-407f-9a23-9de6a8e3edb5 · outbound

This paper cites Metasym: A symplectic meta-learning framework for physical intelligence,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Metasym: A symplectic meta-learning framework for physical intelligence,

Reference 30

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Observation 57a34e22-0fab-4d6d-8764-94a3c091cac4 · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 31

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Structure-preserving neural networks,

Reference 32

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This paper cites Multi-contact inertial param- eters estimation and localization in legged robots,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Multi-contact inertial param- eters estimation and localization in legged robots,

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Observation 0add5df5-ded8-492a-ae2f-aa6a87908a5d · outbound

This paper cites System identification under constraints and disturbance: A bayesian estimation approach,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts System identification under constraints and disturbance: A bayesian estimation approach,

Reference 34

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Observation f2b1052c-4011-48d3-a9b3-7aa6135f64b0 · outbound

This paper cites Recurrent world models facilitate policy evolution,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Recurrent world models facilitate policy evolution,

Reference 35

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Learning to simulate complex physics with graph networks,

Reference 36

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This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Fourier Neural Operator for Parametric Partial Differential Equations

Reference 37

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Observation a7f37e67-06b1-466a-9398-d53afbdb9b2c · outbound

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Fourier neural operator with learned deformations for pdes on general geometries,

Reference 38

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Observation 0a47ff34-afe2-4df3-907e-0707758c4170 · outbound

This paper cites Robotic world model: A neural network simulator for robust policy optimization in robotics,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Robotic world model: A neural network simulator for robust policy optimization in robotics,

Reference 39

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Observation da824f07-c5a2-41e6-8c6f-64380c584bf2 · outbound

This paper cites Backpropagation through time: what it does and how to do it,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Backpropagation through time: what it does and how to do it,

Reference 40

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Observation 9adf69bb-1c57-4e06-853f-2998d255524b · outbound

This paper cites On the difficulty of training Recurrent Neural Networks.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts On the difficulty of training Recurrent Neural Networks

Reference 41

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Observation 41e25c99-9582-4c99-a524-2e62cb3a83af · outbound

This paper cites Port-controlled hamiltonian systems: Modelling origins and systemtheoretic properties,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Port-controlled hamiltonian systems: Modelling origins and systemtheoretic properties,

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Observation 4c59c7b7-a829-4413-a5a0-d74d3bff0a9f · outbound

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Bracket formulation for irreversible classical fields,

Reference 43

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Observation aed72f83-82af-4cbc-8a0e-333f05d3099b · outbound

This paper cites Dirac structures in lagrangian mechanics part i: Implicit lagrangian systems,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Dirac structures in lagrangian mechanics part i: Implicit lagrangian systems,

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This paper cites Abraham and J.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Abraham and J

Reference 45

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Observation 70a028b5-181c-4869-8ebe-0f19d8c25fed · outbound

This paper cites On Symplectic Optimization.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts On Symplectic Optimization

Reference 46

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Observation c6af31cb-26cf-4ccb-975a-fb25941d039e · outbound

This paper cites Learning physical systems: Symplectification via gauge fixing in dirac structures,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Learning physical systems: Symplectification via gauge fixing in dirac structures,

Reference 47

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Observation 4407e284-b223-4cee-81c3-97e0aa6dd7dc · outbound

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Kolmogorov’s spline network,

Reference 48

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Observation e7d3be48-318b-42a2-a468-1116c2b4691c · outbound

This paper cites KAN 2.0: Kolmogorov-Arnold Networks Meet Science.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts KAN 2.0: Kolmogorov-Arnold Networks Meet Science

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Observation e0b0402f-8f27-45a7-a33f-2e574244724e · outbound

This paper cites A recursive newton-euler algorithm for robots with elastic joints and its application to control,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts A recursive newton-euler algorithm for robots with elastic joints and its application to control,

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Observation 56943ca9-aa66-451c-a803-b76ebefd9621 · outbound

This paper cites The calculation of robot dynamics using articulated- body inertias,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts The calculation of robot dynamics using articulated- body inertias,

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Observation a09efe35-32ec-4a5d-9099-a2d349378e61 · outbound

This paper cites Goldstein, C.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Goldstein, C

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Observation c353a058-c659-4300-a843-c0fca07748eb · outbound

This paper cites A micro Lie theory for state estimation in robotics.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts A micro Lie theory for state estimation in robotics

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Observation 6cee9161-d280-4f95-9d9a-2078bba29523 · outbound

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Guillemin and S

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Observation 3fac2c03-6cc0-448f-8798-ef2de1f68913 · outbound

This paper cites Weinstein,Lectures on symplectic manifolds.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Weinstein,Lectures on symplectic manifolds

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Observation 355e6a77-d315-4d98-8a95-8752260205dd · outbound

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Unresolved cited work

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Unresolved cited work

Reference 57

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Observation 2a34db61-8bb7-4e5c-8c28-909ed6bf294e · outbound

This paper cites Anymal - a highly mo- bile and dynamic quadrupedal robot,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Anymal - a highly mo- bile and dynamic quadrupedal robot,

Reference 58

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Observation 578d8bb7-480e-4c57-a4ed-43c002aede57 · outbound

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Professor forcing: A new algorithm for training recurrent networks,

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Observation 1a5eb14b-9b66-4bcd-90ba-566141880956 · outbound

This paper cites Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion

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This paper cites Symplectic Neural Networks Based on Dynamical Systems.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Symplectic Neural Networks Based on Dynamical Systems

Reference 61

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Efficiently Parameterized Neural Metriplectic Systems

Reference 62

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Dissipative hamiltonian neural networks: Learning dissipative and conservative dynamics separately,

Reference 63

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Observation 9981f500-4ed4-433f-b1f2-b8788cf91475 · outbound

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning

Reference 64

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Deep learning a quadro- tor dynamic model for multi-step prediction,

Reference 65

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Observation b8f353b4-a191-43ca-b0ca-be6107dd8a7c · outbound

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Multistep prediction of dynamic systems with recurrent neural networks,

Reference 66

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This paper cites A review of quadruped robots: Structure, control, and autonomous motion,.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts A review of quadruped robots: Structure, control, and autonomous motion,

Reference 67

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Observation fc8358e3-cae6-4a7f-b590-4ec40251d48b · outbound

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts GrandTour: A Legged Robotics Dataset in the Wild for Multi-Modal Perception and State Estimation

Reference 68

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Observation dcfb5a44-28b2-42fd-a51a-e4faaac09ac2 · outbound

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CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Safe Learning in Robotics: From Learning-Based Control to Safe Reinforcement Learning

Reference 69

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Observation 6e4c7d8e-ac81-44f2-82ea-11b459ab146a · outbound

This paper cites Professor Forcing: A New Algorithm for Training Recurrent Networks.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Professor Forcing: A New Algorithm for Training Recurrent Networks

Reference 2016

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This paper cites Dissipative Hamiltonian Neural Networks: Learning Dissipative and Conservative Dynamics Separately.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Dissipative Hamiltonian Neural Networks: Learning Dissipative and Conservative Dynamics Separately

Reference 2022

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Observation 840c19f0-b5cd-47a1-a332-1b14bb5e0d40 · outbound

This paper cites Available: https://advanced.onlinelibrary.wiley.com/doi/ abs/10.1002/aisy.202300385.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Available: https://advanced.onlinelibrary.wiley.com/doi/ abs/10.1002/aisy.202300385

Reference 2024

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