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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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7 results for “SRV”

High-resolution Markov state models for the dynamics of Trp-cage miniprotein constructed over slow folding modes identified by state-free reversible VAMPnetsphysics.bio-ph

SRVs improve MSMs for Trp-cage miniprotein, revealing new folding states.

problem Constructing high-resolution MSMs for complex protein dynamics.

method Employing SRVs as feature set for MSM construction, leveraging slowest modes identified by SRVs.

result SRV-MSMs reveal new folding states and faster convergence.

SRVs MSM Trp-cage protein dynamics folding kinetics

2019-06-12abs ↗pdf ↗

Nonlinear Discovery of Slow Molecular Modes using State-Free Reversible VAMPnetsstat.ML

SRV learns slow molecular modes from simulations.

problem Discovering slow collective motions in molecular dynamics.

method State-free reversible VAMPnets (SRV) for nonlinear CV approximation.

result SRVs capture slow dynamics in complex systems.

deep learning molecular dynamics collective variables eigenfunctions SRV

2019-02-09abs ↗pdf ↗

Reparameterization invariant metric on the space of curvesmath.DG

This paper focuses on the study of open curves in a manifold M, and proposes a reparameterization invariant metric on the space of such paths. We use the square root velocity function (SRVF) introduced by Srivastava et al. in [11] to define a reparameterization invariant metric on the space of immersions M' = Imm([0,1]…

2015-07-23abs ↗pdf ↗

Computing distances and geodesics between manifold-valued curves in the SRV frameworkmath.DG

This paper focuses on the study of open curves in a Riemannian manifold M, and proposes a reparametrization invariant metric on the space of such paths. We use the square root velocity function (SRVF) introduced by Srivastava et al. to define a Riemannian metric on the space of immersions M'=Imm([0,1],M) by pullback of…

2016-01-11abs ↗pdf ↗

Signatures in Shape Analysis: an Efficient Approach to Motion Identificationmath.DG

A new method uses signatures to classify shapes efficiently.

problem Classifying shapes succinctly and invariantly.

method Proposes a method using signatures for shape classification.

result Outperforms current methods like SRV transform and dynamic programming.

signatures shape classification motion identification reparametrization invariant

2019-06-14abs ↗pdf ↗

Capabilities and Limitations of Time-lagged Autoencoders for Slow Mode Discovery in Dynamical Systemsstat.ML

TAEs discover slow modes but mix them with max variance modes.

problem Discovering slow modes in dynamical systems.

method Theoretical and numerical analysis of TAEs.

result TAEs learn a mixture of slow and max variance modes.

Time-lagged autoencoders slow modes dynamical systems deep learning variational methods

2019-06-02abs ↗pdf ↗

Elastic Metrics on Spaces of Euclidean Curves: Theory and Algorithmsmath.DG

Unified treatment of elastic metrics for curves in any dimension.

problem Defining metrics on spaces of Euclidean curves for statistical analysis.

method Developing a unified approach to elastic metrics, extending results on existence of solutions and algorithms for computing distances and geodesics.

result Unified treatment of elastic metrics for all parameter choices, extending previous work.

Elastic metrics Euclidean curves Statistical shape analysis Registration Geodesics

2022-09-20abs ↗pdf ↗