On-device research index

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.

168,742 papers · 148 categories

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48 results for “multiple trajectories”

Learning the Dynamics of Autonomous Linear Systems From Multiple Trajectorieseess.SY

Study learns dynamics of linear systems from multiple short trajectories.

problem Learning dynamics of autonomous linear systems from multiple short trajectories.

method Finite sample analysis for stable and unstable systems, adjusting trajectory length for marginally stable systems.

result Learning rate of

\mathcal{O}(\frac{1}{\sqrt{N}})

for both stable and unstable systems.

linear systems autonomous finite sample analysis multiple trajectories learning dynamics

2022-03-24abs ↗pdf ↗

Multi-Modal Trajectory Prediction of NBA Playerscs.LG

Method predicts NBA players' multi-modal movement trajectories.

problem Understanding NBA players' decision-making during games.

method LSTM-based architecture with multi-modal loss function.

result Method outperforms state-of-the-art in predicting realistic trajectories.

NBA players trajectory prediction multi-modal behavior LSTM decision making

2020-08-18abs ↗pdf ↗

Multiple Futures Predictioncs.LG

Predicts multiple vehicle trajectories efficiently.

problem Predicting uncertain future motions of agents in dynamic scenes.

method Probabilistic framework learning latent variables for multi-step future modeling.

result State-of-the-art predictions on vehicle trajectory datasets.

motion prediction probabilistic modeling latent variables multi-agent interactions conditional probability

2019-11-04abs ↗pdf ↗

Collaborative Uncertainty Benefits Multi-Agent Multi-Modal Trajectory Forecastingcs.CV

This work tackles uncertainty in multi-agent multi-modal trajectory forecasting.

problem Measuring and ranking uncertainty in multi-agent multi-modal trajectory forecasting.

method Proposes collaborative uncertainty (CU) and a CU-aware regression framework.

result The CU-aware regression framework improves SOTA systems' performances.

uncertainty multi-agent multi-modal trajectory forecasting permutation-equivariant

2022-07-11abs ↗pdf ↗

Learning Linearized Models from Nonlinear Systems with Finite Dataeess.SY

We learn linear models from nonlinear systems using multiple trajectories and regularization.

problem Identifying linear models from data when the underlying dynamics are nonlinear.

method Multiple trajectories data acquisition followed by regularized least squares.

result Learn linearized dynamics with arbitrarily small error given enough samples.

linear system identification nonlinear dynamics finite sample analysis multiple trajectories regularized least squares

2023-09-15abs ↗pdf ↗

SafeMIL: Learning Offline Safe Imitation Policy from Non-Preferred Trajectoriescs.LG

SafeMIL learns safer policies by avoiding risky behavior from non-preferred trajectories.

problem Learning safe imitation policies from non-preferred trajectories in risky environments.

method SafeMIL uses Multiple Instance Learning to learn a cost function from non-preferred trajectories.

result SafeMIL learns a safer policy that avoids non-preferred behaviors without sacrificing reward performance.

safe imitation offline learning risk avoidance multiple instance learning non-preferred trajectories

2025-11-11abs ↗pdf ↗

Learning interaction kernels in heterogeneous systems of agents from multiple trajectoriesstat.ML

Paper learns interaction laws from multiple trajectories of heterogeneous systems.

problem Estimating unknown interaction laws from multiple trajectories of heterogeneous systems.

method Nonparametric learning of interaction kernels based on pairwise distances, with convergence guarantees in

L^2

space.

result Estimators converge at optimal min-max rate for 1-dimensional nonparametric regression.

interaction kernels heterogeneous systems multiple trajectories nonparametric learning pairwise distances

2019-10-10abs ↗pdf ↗

Learning Mixtures of Linear Dynamical Systemsstat.ML

Algorithm learns multiple LDS models from unlabeled short trajectories.

problem Learning from unlabeled short sample trajectories of multiple LDS models.

method Two-stage meta-algorithm with end-to-end performance guarantees.

result Efficiently recovers each ground-truth LDS model up to error

ilde{O}(\sqrt{d/T})

Mixture Models Linear Dynamical Systems Time-Series Data Unlabeled Data Meta-Algorithms

2022-01-26abs ↗pdf ↗

Multi-Marginal Schrödinger Bridge Matchingstat.ML

MSBM extends SB for multi-marginal trajectory inference.

problem Trajectory inference from multiple discrete snapshots.

method Multi-Marginal Schrödinger Bridge Matching (MSBM) using iterative Markovian fitting (IMF).

result MSBM effectively captures complex trajectories and respects intermediate distributions.

Schrödinger Bridge trajectory inference multi-marginal single-cell RNA sequencing developmental biology

2025-10-18abs ↗pdf ↗

Attention-Bayesian Hybrid Approach to Modular Multiple Particle Trackingstat.ML

Hybrid approach combines transformer and Bayesian filtering for robust multiple particle tracking.

problem Challenges in tracking multiple particles in noisy scenes due to combinatorial explosion of hypotheses.

method Attention-Bayesian hybrid framework using transformer for association and Bayesian filtering for pruning hypotheses.

result Improved tracking accuracy and robustness against spurious detections.

multiple particle tracking transformer Bayesian filtering label prediction soft associations

2025-06-11abs ↗pdf ↗

CMTS: Conditional Multiple Trajectory Synthesizer for Generating Safety-critical Driving Scenarioscs.LG

Naturalistic driving trajectories are crucial for the performance of autonomous driving algorithms. However, most of the data is collected in safe scenarios leading to the duplication of trajectories which are easy to be handled by currently developed algorithms. When considering safety, testing algorithms in near-miss…

2019-09-17abs ↗pdf ↗

Using simplicial volume to count multi-tangent trajectories of traversing vector fieldsmath.DG

For a non-vanishing gradient-like vector field on a compact manifold $X^{n+1}$ with boundary, a discrete set of trajectories may be tangent to the boundary with reduced multiplicity $n$ , which is the maximum possible. (Among them are trajectories that are tangent to $\partial X$ exactly $n$ times.) We prove a lower bou…

2015-03-09abs ↗pdf ↗

Applying Recent Innovations from NLP to MOOC Student Course Trajectory Modelingcs.LG

Paper improves neural network models for MOOC student course prediction.

problem Improving neural network-based predictive methods for MOOC student course trajectory modeling.

method Enhanced LSTM networks and Transformer architecture applied to MOOC student data.

result Improved accuracy in predicting MOOC student course trajectories.

MOOC student trajectory course prediction LSTM Transformer

2020-01-23abs ↗pdf ↗

Mobility Inference on Long-Tailed Sparse Trajectorycs.LG

Paper infers human mobility from sparse trajectories.

problem Modeling and inferring human mobility from sparse trajectory data.

method Proposes a single trajectory inference algorithm and a deep learning architecture for multiple trajectories.

result Deep learning model achieves 2x overall accuracy improvement on sparse trajectories.

Mobility Inference Sparse Trajectories Deep Learning Sequence Learning Urban Trajectories

2020-01-21abs ↗pdf ↗

Multi-marginal Schrödinger Bridges with Iterative Reference Refinementstat.ML

New method learns cell trajectories from multiple snapshots.

problem Inferring cell trajectories from limited, single-time-point data.

method Multi-marginal Schrödinger Bridges with iterative reference refinement.

result Effective in capturing long-term dependencies and learning from multiple time points.

Schrödinger Bridges cell trajectories multi-marginal deep learning single-cell sequencing

2024-08-12abs ↗pdf ↗

SafeCritic: Collision-Aware Trajectory Predictioncs.LG

SafeCritic predicts safe trajectories for pedestrians and cyclists avoiding collisions.

problem Predicting safe trajectories for pedestrians and cyclists in urban environments.

method Generative adversarial networks and reinforcement learning to generate safe trajectories, evaluated by a Discriminator.

result Significant improvement over state-of-the-art models in safety classification.

autonomous systems trajectory prediction pedestrians cyclists collision avoidance

2019-10-15abs ↗pdf ↗

Longitudinal Flow Matching for Trajectory Modelingcs.LG

Framework learns continuous dynamics from sparse trajectories.

problem Learning dynamics from sparsely sampled and high-dimensional trajectories.

method Interpolative Multi-Marginal Flow Matching (IMMFM) framework.

result IMMFM outperforms existing methods in forecasting and downstream tasks.

flow matching trajectory modeling stochastic dynamics sparse sampling neuroimaging

2025-10-03abs ↗pdf ↗

EviTrack: Selection over Sampling for Delayed Disambiguationcs.LG

EviTrack improves sequential prediction in delayed disambiguation scenarios.

problem Challenges in sequential prediction with delayed disambiguation where early observations are ambiguous.

method EviTrack operates over latent trajectories, applying evidence- and likelihood-ratio-based selection to delay commitment until supported by data.

result EviTrack outperforms sampling-based baselines in a controlled synthetic benchmark, achieving faster post-disambiguation recovery.

sequential prediction delayed disambiguation latent trajectories hypothesis selection likelihood-ratio

2026-05-19abs ↗pdf ↗

Variational Autoencoding the Lagrangian Trajectories of Particles in a Combustion Systemstat.ML

We introduce a deep learning method to simulate the motion of particles trapped in a chaotic recirculating flame. The Lagrangian trajectories of particles, captured using a high-speed camera and subsequently reconstructed in 3-dimensional space, were used to train a variational autoencoder (VAE) which comprises multipl…

2018-11-29abs ↗pdf ↗

Function-Space Priors for Bayesian Neural ODEs with Application to Vessel Trajectory Predictionstat.ML

Bayesian Neural ODEs improve vessel trajectory prediction with better uncertainty estimates.

problem Challenges in predicting vessel trajectories from irregular AIS data.

method Adopted a Gaussian process (GP) kernel-based prior on the vector field evaluated at measurement points, combined with probabilistic multiple shooting for long trajectories.

result Improved accuracy and uncertainty quantification in vessel trajectory predictions.

Bayesian Neural ODEs Vessel Trajectory Prediction Automatic Identification System (AIS)Kernel-based Regularization Probabilistic Multiple Shooting

2026-06-04abs ↗pdf ↗

PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goalscs.LG

PlanGAN uses GANs to plan efficient trajectories for multi-goal tasks in sparse reward environments.

problem Learning with sparse rewards in multi-goal environments.

method PlanGAN combines GANs to generate trajectories leading to specified goals, then combines these into a planning algorithm.

result PlanGAN achieves comparable performance to model-free RL but is 4-8 times more sample efficient.

model-based planning sparse rewards multi-goal tasks GANs reinforcement learning

2020-06-01abs ↗pdf ↗

Ambiguity in Sequential Data: Predicting Uncertain Futures with Recurrent Modelsstat.ML

Proposes handling ambiguity in sequential data predictions.

problem Handling uncertainty in sequential data predictions.

method Extension of MHP model to recurrent architectures, introducing a novel metric.

result Achieved promising results on various sequential data tasks.

ambiguity sequential data recurrent models multiple hypotheses trajectory forecasting

2020-03-10abs ↗pdf ↗

Trajectory Optimization for Unknown Constrained Systems using Reinforcement Learningstat.ML

In this paper, we propose a reinforcement learning-based algorithm for trajectory optimization for constrained dynamical systems. This problem is motivated by the fact that for most robotic systems, the dynamics may not always be known. Generating smooth, dynamically feasible trajectories could be difficult for such sy…

2019-03-13abs ↗pdf ↗

Reinforcement Learning with Random Time Horizonscs.LG

Extends RL to random stopping times, improving optimization.

problem Real-world applications with random stopping times.

method Extended RL framework to random stopping times, derived new formulas.

result Improves optimization convergence with new formulas.

Reinforcement Learning Random Time Horizons Policy Gradient Optimal Control Trajectory-Based

2025-06-01abs ↗pdf ↗

Minimizing Trajectory Curvature of ODE-based Generative Modelscs.LG

Efficiently trains forward processes to minimize generative trajectories curvature.

problem High curvature of generative trajectories slows down sampling speed.

method Trains forward process to minimize curvature without ODE/SDE simulation.

result Lower curvature than previous models, decreased sampling costs.

ODE SDE Generative Models Trajectory Curvature Sampling Speed

2023-01-27abs ↗pdf ↗

MultiPath: Multiple Probabilistic Anchor Trajectory Hypotheses for Behavior Predictioncs.LG

MultiPath predicts multi-modal future trajectories for better motion planning.

problem Predicting human behavior in uncertain real-world domains like autonomous driving.

method Leverages fixed future state-sequence anchors and regresses offsets with uncertainties.

result Achieves more accurate predictions with an order of magnitude fewer trajectories.

behavior prediction motion planning autonomous driving multi-modal distribution probabilistic trajectory

2019-10-12abs ↗pdf ↗

MPE: A Mobility Pattern Embedding Model for Predicting Next Locationscs.LG

MPE models traffic trajectory data to predict next locations.

problem Predicting next locations from traffic trajectory data.

method Mobility pattern embedding model MPE.

result MPE significantly outperforms state-of-the-art methods in next location prediction.

mobility pattern trajectory data next location prediction phantom transitions low-dimensional latent space

2020-03-16abs ↗pdf ↗

SyncSDE: A Probabilistic Framework for Diffusion Synchronizationcs.LG

Paper presents a probabilistic framework for diffusion synchronization.

problem Improper application of heuristics leads to suboptimal results in diffusion synchronization.

method Develops a probabilistic framework to analyze and adapt correlation models for each specific task.

result Achieves better results by identifying optimal correlation models per task.

diffusion synchronization probabilistic framework correlation models task-specific adaptation

2025-03-27abs ↗pdf ↗

Conformalized Adaptive Forecasting of Heterogeneous Trajectoriesstat.ML

New method for predicting paths of unpredictable objects with high confidence.

problem Need for dependable uncertainty estimates in motion planning with diverse unpredictable objects.

method Blend online conformal prediction, multiple time series techniques, and heteroscedasticity addressing.

result Simultaneous forecasting bands that cover entire paths with high probability.

conformal prediction heterogeneous trajectories motion planning uncertainty estimation

2024-02-14abs ↗pdf ↗

Coordination and Trajectory Prediction for Vehicle Interactions via Bayesian Generative Modelingcs.RO

Coordination recognition and subtle pattern prediction of future trajectories play a significant role when modeling interactive behaviors of multiple agents. Due to the essential property of uncertainty in the future evolution, deterministic predictors are not sufficiently safe and robust. In order to tackle the task o…

2019-05-02abs ↗pdf ↗

PhysVarMix: Physics-Informed Variational Mixture Model for Multi-Modal Trajectory Predictioncs.RO

PhysVarMix predicts diverse urban trajectories with physics constraints.

problem Predicting complex urban agent trajectories with multiple plausible scenarios.

method Physics-informed variational mixture model combining learning and physics constraints.

result Superior performance compared to existing methods on benchmark datasets.

trajectory prediction autonomous driving multi-modality physics-informed variational Bayesian

2025-07-25abs ↗pdf ↗

Advance Real-time Detection of Traffic Incidents in Highways using Vehicle Trajectory Datacs.CY

Study uses vehicle trajectory data to predict traffic incidents on highways.

problem Early detection of traffic incidents to reduce secondary crashes.

method Machine learning algorithms (Logistic Regression, Random Forest, Extreme Gradient Boost, Artificial Neural Network) applied to vehicle trajectory data.

result Random Forest model performs best for incident prediction.

traffic incidents vehicle trajectories machine learning highway safety predictive analytics

2024-08-15abs ↗pdf ↗

Image Evolution Trajectory Prediction and Classification from Baseline using Learning-based Patch Atlas Selection for Early Diagnosiseess.IV

Patients initially diagnosed with early mild cognitive impairment (eMCI) are known to be a clinically heterogeneous group with very subtle patterns of brain atrophy. To examine the boarders between normal controls (NC) and eMCI, Magnetic Resonance Imaging (MRI) was extensively used as a non-invasive imaging modality to…

2019-07-13abs ↗pdf ↗

Synthetic Survival Control: Extending Synthetic Controls for "When-If" Decisioncs.LG

Proposes SSC for estimating counterfactual survival trajectories from observational data.

problem Challenges in estimating causal effects on time-to-event outcomes from observational data.

method Synthetic Survival Control (SSC) framework for estimating counterfactual hazard trajectories in panel data settings.

result SSC estimates counterfactual hazard trajectories as a weighted combination of observed trajectories from other units.

Synthetic Survival Control Causal Survival Analysis Observational Data Time-to-Event Outcomes Counterfactual Inference

2025-11-18abs ↗pdf ↗

Learning from many trajectoriescs.LG

Study of supervised learning from multiple non-independent sequences.

problem Efficient learning from many non-independent sequences.

method Generalizes conditions for efficient learning from independent examples and single auto-correlated sequences.

result Error rate changes from

Θ(n / m T)

Ω(n^2 / m^2 T)

as the number of trajectories increases.

supervised learning non-independent sequences statistical learning sequence modeling reinforcement learning

2022-03-31abs ↗pdf ↗

Interacting Particle Systems on Networks: joint inference of the network and the interaction kernelstat.ML

Estimates network structure and interaction rules from multiple agent trajectories.

problem Modeling multi-agent systems on networks from data.

method Jointly infers network topology and interaction kernels using non-convex optimization.

result ORALS estimator is consistent and asymptotically normal under coercivity conditions.

interacting particle systems network inference non-convex optimization alternating least squares operator regression

2024-02-13abs ↗pdf ↗

Deep learning based numerical approximation algorithms for stochastic partial differential equationsmath.NA

Deep learning approximates SPDE solutions from noise trajectories.

problem Approximating solutions to stochastic partial differential equations (SPDEs).

method Uses neural networks to approximate SPDE solutions based on noise realizations.

result Accurately estimates SPDE solutions and functionals like mean and variance.

deep learning stochastic partial differential equations numerical approximation neural networks SPDE solutions

2020-12-02abs ↗pdf ↗

Flowing with Confidencestat.ML

Generative models need per-sample confidence scores to improve quality and stability.

problem Generative models produce unreliable outputs and lack confidence measures.

method Flow Matching with Confidence (FMwC) injects noise and integrates it through the network, providing per-sample confidence scores.

result The confidence score correlates with the velocity field's divergence, offering insights into generative processes.

generative models confidence scores per-sample evaluation flow matching confidence integration

2026-05-18abs ↗pdf ↗

Model-based Validation as Probabilistic Inferencecs.RO

Bayesian inference models failure distributions in autonomous systems.

problem Estimating the distribution of failures in complex systems.

method Bayesian inference using system dynamics rollouts and gradient computation.

result Improves sample efficiency and parameter space coverage in autonomous systems.

Bayesian inference autonomous systems failure distribution sequential systems Hamiltonian Monte Carlo

2023-05-17abs ↗pdf ↗

Learning distributions of shape trajectories from longitudinal datasets: a hierarchical model on a manifold of diffeomorphismscs.CV

We propose a method to learn a distribution of shape trajectories from longitudinal data, i.e. the collection of individual objects repeatedly observed at multiple time-points. The method allows to compute an average spatiotemporal trajectory of shape changes at the group level, and the individual variations of this tr…

2018-03-27abs ↗pdf ↗

Chain-of-Trajectories: Unlocking the Intrinsic Generative Optimality of Diffusion Models via Graph-Theoretic Planningcs.LG

CoTj improves diffusion model quality and stability via graph planning.

problem Rigidity in diffusion models due to high-dimensional state space.

method Chain-of-Trajectories (CoTj) framework using Diffusion DNA for graph planning.

result CoTj discovers context-aware trajectories improving output quality and stability.

diffusion models graph planning trajectory optimization resource allocation

2026-03-16abs ↗pdf ↗

Nearly Instance-Optimal Parameter Recovery from Many Trajectories via Hellinger Localizationcs.LG

New method improves learning from multiple correlated data trajectories.

problem Learning from multiple correlated data trajectories without mixing assumptions.

method Hellinger localization framework for maximum likelihood estimation.

result Instance-optimal bounds that scale with full data budget under broad conditions.

Hellinger localization maximum likelihood estimation multi-trajectory learning sequential learning parameter recovery

2025-10-07abs ↗pdf ↗

Multi-view diffusion geometry using intertwined diffusion trajectoriescs.LG

Unified framework for multi-view diffusion geometries using intertwined diffusion trajectories.

problem Constructing multi-view diffusion geometries with flexible view interaction and fusion.

method Intertwined multi-view diffusion trajectories (MDTs) as a class of inhomogeneous diffusion processes.

result Established theoretical properties and derived diffusion distances and embeddings.

multi-view diffusion diffusion trajectories manifold learning data clustering random walk operators

2025-12-01abs ↗pdf ↗

Learning interaction kernels in stochastic systems of interacting particles from multiple trajectoriesmath.ST

Study infers interaction kernels from multiple particle trajectories.

problem Inferring interaction kernels from multiple particle trajectories in stochastic systems.

method Nonparametric inference approach based on regularized maximum likelihood estimator.

result Consistent estimator with near-optimal learning rate independent of state space dimension.

particle systems stochastic dynamics interaction kernels inverse problem nonparametric regression

2020-07-30abs ↗pdf ↗

ProtoryNet - Interpretable Text Classification Via Prototype Trajectoriescs.LG

ProtoryNet interprets text sequences using prototype trajectories for better understanding.

problem Improving text classification interpretability and accuracy.

method ProtoryNet uses prototype trajectories to interpret text sequences, with prototype pruning for better interpretability.

result ProtoryNet outperforms baseline models and reduces performance gap compared to black-box models.

text classification interpretability prototype trajectories deep learning RNN

2020-07-03abs ↗pdf ↗

Optimal growth trajectories with finite carrying capacityq-fin.PM

We consider the problem of finding optimal strategies that maximize the average growth-rate of multiplicative stochastic processes. For a geometric Brownian motion the problem is solved through the so-called Kelly criterion, according to which the optimal growth rate is achieved by investing a constant given fraction o…

2015-10-17abs ↗pdf ↗

XJTLUIndoorLoc: A New Fingerprinting Database for Indoor Localization and Trajectory Estimation Based on Wi-Fi RSS and Geomagnetic Fieldcs.LG

In this paper, we present a new location fingerprinting database comprised of Wi-Fi received signal strength (RSS) and geomagnetic field intensity measured with multiple devices at a multi-floor building in Xi'an Jiatong-Liverpool University, Suzhou, China. We also provide preliminary results of localization and trajec…

2018-10-17abs ↗pdf ↗

Pixel personality for dense object tracking in a 2D honeybee hivecs.CV

Tracking large numbers of densely-arranged, interacting objects is challenging due to occlusions and the resulting complexity of possible trajectory combinations, as well as the sparsity of relevant, labeled datasets. Here we describe a novel technique of collective tracking in the model environment of a 2D honeybee hi…

2018-12-31abs ↗pdf ↗