Automatic detection of reflective thinking in math problem solving using body movement data.
problem Detecting reflective thinking in children's mathematical problem solving.
method WeDraw-1 Movement Dataset, Long Short-Term Memory neural networks, end-to-end detection.
result Average F1 scores of 0.73 for automatic detection and 0.79 for end-to-end detection of reflective thinking.
A neural network model mimics body functions for movement tasks.
problem Solving inverse and forward kinematics, dynamics for a redundant manipulator.
method Recurrent neural network with Mean of Multiple Computations principle, dynamic extension.
result Neural network solves inverse tasks and shows prototypical population-coding.
Deep learning detects protective movement behavior in chronic pain patients.
problem Detecting protective movement behavior in chronic pain patients for intervention.
method End-to-end deep learning architecture named BodyAttentionNet (BANet) that learns temporal and bodily parts.
result Statistically significant improvements in detecting protective behavior using attention mechanisms.
New model simplifies symmetry handling in generative AI.
problem Symmetry handling in generative models for scientific tasks.
method Quotient-space diffusion models, viewing symmetry as quotient space.
result Improves performance over existing methods for molecular structure generation.
Visualizes movement control optimization landscapes to understand why it's hard and how to make it easier.
problem Understanding and optimizing movement control problems in animation research.
method Novel visualizations of high-dimensional control optimization landscapes.
result Trajectory optimization becomes increasingly ill-conditioned with longer trajectories, while parameterizing control as partial target states can act as an efficient preconditioner.
Automated GMA using accelerometers detects abnormal infant movements with human-level accuracy.
problem Undetected perinatal stroke leads to lifelong disability.
method Wearable accelerometers and Discriminative Pattern Discovery (DPD) for automated GMA.
result Automated method correctly identifies abnormal movements with human-level accuracy.
A deep learning framework assesses physical rehabilitation exercises.
problem Lack of versatile, robust, and practical assessment methods for rehabilitation exercises.
method Deep learning framework with metrics, scoring functions, and neural networks.
result First implementation of deep neural networks for rehabilitation performance assessment.
Smartwatch HRV measurements improved with machine learning.
problem Systematic error in HRV measurements from consumer smartwatches.
method Explanatory and predictive modeling using accelerometer data.
result Error in HRV measurements can be minimized by machine learning.
New algorithm SFHC achieves near-optimal costs with predictions for non-convex optimization.
problem Online optimization with non-convex hitting costs and movement costs.
method Synchronized Fixed Horizon Control (SFHC) algorithm with conditions on hitting and movement costs.
result Synchronized Fixed Horizon Control (SFHC) achieves a 1+O(1/w) competitive ratio for near-optimal costs. Interfacing a kinetic action of a person to an action of a machine system is an important research topic in many application areas. One of the key factors for intimate human-machine interaction is the ability of the control algorithm to detect and classify different user commands with shortest possible latency, thus ma…
In this paper we propose the time-dependent generalization of an `ordinary' autonomous human biomechanics, in which total mechanical + biochemical energy is not conserved. We introduce a general framework for time-dependent biomechanics in terms of jet manifolds associated to the extended musculo-skeletal configuration…
Robot learns agile leg movements from simulations to real robots.
problem Training legged robots for dynamic maneuvers is challenging and expensive.
method Simulation-based reinforcement learning for real legged systems.
result ANYmal robot can follow high-level commands, run faster, and recover from falls.
Quantum algorithms improve stock price prediction accuracy.
problem Improving stock price prediction accuracy using quantum techniques.
method Extracted stock price indicators, used QA and PCA for feature selection and dimensionality reduction, trained QSVM for binary classification.
result Quantum Support Vector Machine (QSVM) outperformed classical models in stock price prediction accuracy.
Wearable smart suit tracks infant movements with high accuracy.
problem Early detection of atypical motor development in infants.
method Developed a multi-sensor smart suit for data collection, trained a deep CNN algorithm for automatic posture and movement classification.
result Setup achieves human equivalent accuracy in infant posture and movement classification.
Paper reduces movement primitive dimensionality in parameter space.
problem High dimensionality of movement primitives makes policy optimization expensive.
method Investigates dimensionality reduction in parameter space, identifying principal movements.
result Dimensionality reduction in parameter space is more effective than in configuration space.
New illumination bodies defined for ball-convex shapes, proving convexity and establishing surface area measures.
problem Characterizing properties of ball-convex shapes.
method Introducing illumination bodies and weighted illumination bodies, proving convexity, and establishing surface area measures.
result Illumination bodies are convex and provide surface area measures for ball-convex shapes.
Deep convolutional architecture identifies eye movements for biometric faster and more accurately.
problem Biometric identification of eye movements for authentication.
method Developed a deep convolutional architecture to process raw eye-tracking signals.
result Achieved a lower error rate by one order of magnitude and faster identification time by two orders of magnitude.
We recast the Calabi flow in DeGiorgi's language of minimizing movements. We establish the long time existence of minimizing movements for K-energy with arbitrary initial condition. Furthermore we establish some a priori regularity of these solutions, and that sufficiently regular minimizing movements are smooth soluti…
Survey reviews machine learning for automatic movement generation.
problem Need for automatic movement animation in interactive media.
method Machine learning techniques and motion capture data.
result Discussion of research gaps and challenges for future work.
Taureau uses Twitter sentiment analysis to predict stock market movement.
problem Predicting stock market movement using public opinion on Twitter.
method Obtained historical tweets, filtered and labeled, generated word embeddings, assessed sentiment scores, correlated with stock price movement, designed and evaluated predictive model.
result Taureau can predict stock price movement from lagged sentiment scores.
The paper proves a conjecture about the shape of floating bodies.
problem The shape of bodies of flotation and buoyancy.
method Modern differential geometry techniques.
result If a body of flotation is homothetic to a body of buoyancy, it must be an ellipse.
New material groupoid theory subdivides non-uniform bodies into smoothly uniform parts and isolated points.
problem Lack of differentiability in material bodies leads to non-uniformity.
method Introducing material groupoid and material distribution to study non-uniform bodies rigorously.
result Material bodies can be subdivided into smoothly uniform parts and isolated points.
New index characterizes non-smooth Zoll convex bodies.
problem Characterizing non-smooth Zoll convex bodies.
method Defining systolic S1-index and using it to introduce generalized Zoll convex bodies. result Generalized Zoll convex bodies coincide with classical ones under certain conditions.
New surface area measures defined for ball-convex bodies, leading to entropy and inequalities.
problem Defining and analyzing surface area measures for ball-convex bodies.
method Introducing Lp relative surface areas, proving invariance and inequalities, and using geometric interpretations. result Established inequalities and a new notion of entropy for ball-convex bodies.
The study models market price movement based on investors' expectations.
problem Understanding the dynamics of investors' expectations and market price movement.
method Developed a non-linear evolutionary equation linking investors' expectations and market asset price movement.
result Model predictions co-integrated with asset time series, suggesting potential for price movement forecasting.
Neural nets predict user attention from mouse movements.
problem Predicting user attention from mouse cursor movements.
method Investigated different mouse movement representations and trained neural networks.
result Neural networks outperform handcrafted features for predicting user attention.
The paper finds the unique minimizer of area for hyperbolic bodies with curvature constraints.
problem Finding the unique minimizer of area for hyperbolic bodies with curvature constraints.
method Introduced the concept of 'thick λ-sausage' bodies and used extra assumption of thickness to handle non-convex inner parallel bodies. result The thick λ-sausage body is the unique minimizer of area among all bodies with a given length and curvature constraints. Study shows volumes of complex classes can be represented by convex bodies.
problem Understanding volumes of complex classes on Kähler manifolds.
method Approximation by partial Okounkov bodies, restricted volume properties, and bimeromorphic behavior of currents.
result Volume of transcendental big (1,1)-classes can be realized by convex bodies. Paper proves minimizing movements match smooth droplet flow in 3D.
problem Consistency of minimizing movements with smooth mean curvature flow.
method Proved minimizing movements coincide with smooth droplet flow.
result Minimizing movements and smooth mean curvature flow are consistent in 3D.
A unique volume minimizer is found in a class of convex bodies.
problem Finding a unique minimizer for a reverse isoperimetric problem.
method Proving a reverse quermassintegral inequality.
result The convex hull of two balls is a unique minimizer among λ-concave bodies. MPANF improves naive forecast by incorporating directional information.
problem Challenging to surpass naive forecast in financial time series.
method Combines naive forecast with movement prediction and accuracy.
result MPANF generally outperforms common benchmarks.
Extends illumination bodies to non-Euclidean spaces and proves their volume derivative defines surface area.
problem Defining surface area in non-Euclidean geometries.
method Generalizes illumination bodies to Riemannian spaces of constant curvature and projective Finsler geometries, proving their volume derivative defines surface area.
result Derivative of volume of illumination bodies defines surface area in non-Euclidean geometries.
Solves Alexandrov's problem for hyperbolic convex bodies.
problem Finding a convex body with a given curvature measure in hyperbolic space.
method Defined Gauss curvature measure, proved existence and uniqueness of solution.
result Uniqueness of the solution to Alexandrov's problem in hyperbolic space.
We introduce and study a new class of $\eps$-convex bodies (extending the class of convex bodies) in metric and normed linear spaces. We analyze relations between characteristic properties of convex bodies, demonstrate how $\eps$-convex bodies connect with some classical results of Convex Geometry, as Helly theorem, an…
We propose a Variational Time Series Feature Extractor (VTSFE), inspired by the VAE-DMP model of Chen et al., to be used for action recognition and prediction. Our method is based on variational autoencoders. It improves VAE-DMP in that it has a better noise inference model, a simpler transition model constraining the …
Framework infers coordination strategies from movement data.
problem Inferring individual movement strategies from group data.
method Formalizes Coordination Strategy Inference Problem; provides methodology to infer strategies.
result Framework accurately infers strategies in simulated and real-world datasets.
Neuroscientific studies of drawing-like movements usually analyze neural representation of either geometric (eg. direction, shape) or temporal (eg. speed) features of trajectories rather than trajectory's representation as a whole. This work is about empirically supported mathematical ideas behind splitting and merging…
Study on discrete Okounkov bodies and their applications.
problem Understanding stability and thresholds in higher dimensions.
method Analysis of discrete Okounkov bodies and gap phenomena.
result Asymptotic analysis of stability and thresholds.
Study identifies key trades predicting market movements.
problem Predicting future market price movements.
method Optimized neural network predictor to identify influential trades.
result Trades with specific characteristics significantly impact future price predictions.
The study introduces a new stickiness parameter for stock prices using a non-linear model.
problem Understanding how closely individual stocks follow a stock index's price movements.
method Developed a non-linear pricing model inspired by tectonic plate movements to measure stickiness.
result Defined a stickiness parameter for stock price returns using a novel model.
Analogues of the classical inequalities from the Brunn-Minkowski theory for rotation intertwining additive maps of convex bodies are developed. Analogues are also proved of inequalities from the dual Brunn-Minkowski theory for intertwining additive maps of star bodies. These inequalities provide generalizations of resu…
We consider the motion of small bodies in general relativity. The key result captures a sense in which such bodies follow timelike geodesics (or, in the case of charged bodies, Lorentz-force curves). This result clarifies the relationship between approaches that model such bodies as distributions supported on a curve, …
Prove a generalization of Werner's formula for the volume of illumination bodies on Riemannian manifolds.
problem Prove a generalization of Werner's formula for the volume of illumination bodies on Riemannian manifolds.
method Define the δ-illumination body and prove a generalization of Werner's formula. result Prove a generalization of Werner's formula for the volume of illumination bodies on Riemannian manifolds.
TraLFM models human mobility patterns from traffic trajectories.
problem Understanding human mobility patterns from traffic data.
method Latent factor modeling of sequential, personal, and temporal factors.
result TraLFM significantly outperforms state-of-the-art methods in latent factor analysis and next location prediction.
This paper is dedicated to the Orlicz-Petty bodies. We first propose the homogeneous Orlicz affine and geominimal surface areas, and establish their basic properties such as homogeneity, affine invariance and affine isoperimetric inequalities. We also prove that the homogeneous geominimal surface areas are continuous, …
Bayesian method infers local rules for collective animal movement.
problem Learn local rules governing long-term group behaviors.
method Bayesian Inverse Reinforcement Learning with Linearly-Solvable Markov Decision Process.
result Recover true costs and find value of collective movement.
NoTMF forecasts sparse urban road movement speeds with nonstationary temporal matrix factorization.
problem Sparse and nonstationary movement speed data from urban roads.
method Nonstationary Temporal Matrix Factorization (NoTMF) model.
result NoTMF outperforms baseline models in forecasting urban road movement speeds.
Optimizing data movement significantly improves transformer training efficiency.
problem Data movement is a major bottleneck in training transformers.
method Developed a recipe to globally optimize data movement in transformers.
result Achieved up to 1.30x performance improvement over state-of-the-art frameworks.