Cover Image

TrajFlow: A Generative Framework for Occupancy Density Estimation Using Normalizing Flows

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kosieradzki, Mitch, Choi, Seongjin
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TrajFlow: Nation-wide Pseudo GPS Trajectory Generation with Flow Matching Models
by: Li, Peiran, et al.
Published: (2026)

TrajFlow: Multi-modal Motion Prediction via Flow Matching
by: Yan, Qi, et al.
Published: (2025)

TrajFlow: Learning Distributions over Trajectories for Human Behavior Prediction
by: Mészáros, Anna, et al.
Published: (2023)

Comparing Normalizing Flows with Kernel Density Estimation in Estimating Risk of Automated Driving Systems
by: de Gelder, Erwin, et al.
Published: (2025)

Beyond coauthorship: semantic structure and phantom collaborators in transportation research, 1967--2025
by: Choi, Seongjin
Published: (2026)

Reducing Estimation Uncertainty Using Normalizing Flows and Stratification
by: Lorek, Paweł, et al.
Published: (2026)

PMA-Diffusion: A Physics-guided Mask-Aware Diffusion Framework for TSE from Sparse Observations
by: Liu, Lindong, et al.
Published: (2025)

Fast and Unified Path Gradient Estimators for Normalizing Flows
by: Vaitl, Lorenz, et al.
Published: (2024)

Intention-Conditioned Flow Occupancy Models
by: Zheng, Chongyi, et al.
Published: (2025)

Toward Safe Integration of UAM in Terminal Airspace: UAM Route Feasibility Assessment using Probabilistic Aircraft Trajectory Prediction
by: Cho, Jungwoo, et al.
Published: (2025)

Mutual Information Estimation via Normalizing Flows
by: Butakov, Ivan, et al.
Published: (2024)

Deep Reinforcement Learning for Dynamic Origin-Destination Matrix Estimation in Microscopic Traffic Simulations Considering Credit Assignment
by: Min, Donggyu, et al.
Published: (2025)

Distilling Normalizing Flows
by: Walton, Steven, et al.
Published: (2025)

Preferential Normalizing Flows
by: Mikkola, Petrus, et al.
Published: (2024)

Piecewise Normalizing Flows
by: Bevins, Harry, et al.
Published: (2023)

Normalizing Flow to Augmented Posterior: Conditional Density Estimation with Interpretable Dimension Reduction for High Dimensional Data
by: Zeng, Cheng, et al.
Published: (2025)

A Novel Framework Using Variational Inference with Normalizing Flows to Train Transport Reversible Jump Proposals
by: Yin, Pingping, et al.
Published: (2025)

Conditional Normalizing Flows for Forward and Backward Joint State and Parameter Estimation
by: Lagunowich, Luke S., et al.
Published: (2026)

Principled Interpolation in Normalizing Flows
by: Fadel, Samuel G., et al.
Published: (2020)

Flexible Tails for Normalizing Flows
by: Hickling, Tennessee, et al.
Published: (2024)

Causally Consistent Normalizing Flow
by: Zhou, Qingyang, et al.
Published: (2024)

Normalizing Flows are Capable Generative Models
by: Zhai, Shuangfei, et al.
Published: (2024)

Scalable Normalizing Flows Enable Boltzmann Generators for Macromolecules
by: Kim, Joseph C., et al.
Published: (2024)

Hybrid Bernstein Normalizing Flows for Flexible Multivariate Density Regression with Interpretable Marginals
by: Arpogaus, Marcel, et al.
Published: (2025)

Normalizing Flows for Conformal Regression
by: Colombo, Nicolo
Published: (2024)

Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models
by: Saporiti, Riccardo, et al.
Published: (2026)

Free-form Flows: Make Any Architecture a Normalizing Flow
by: Draxler, Felix, et al.
Published: (2023)

IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecasting
by: Fan, Wei, et al.
Published: (2024)

SenseFlow: A Physics-Informed and Self-Ensembling Iterative Framework for Power Flow Estimation
by: Zhao, Zhen, et al.
Published: (2025)

Weaver: Kronecker Product Approximations of Spatiotemporal Attention for Traffic Network Forecasting
by: Cheong, Christopher, et al.
Published: (2025)

Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows
by: Cabezas, Alberto, et al.
Published: (2024)

Normalizing Flows are Capable Models for RL
by: Ghugare, Raj, et al.
Published: (2025)

Adaptive Epsilon Adversarial Training for Robust Gravitational Wave Parameter Estimation Using Normalizing Flows
by: Yang, Yiqian, et al.
Published: (2024)

Flow-Based Density Ratio Estimation for Intractable Distributions with Applications in Genomics
by: Antipov, Egor, et al.
Published: (2026)

FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering
by: Qin, Juehang, et al.
Published: (2025)

FlowSDR: Sufficient Dimension Reduction via Conditional Normalizing Flows
by: Dong, Yuexiao, et al.
Published: (2026)

PolicyFlow: Policy Optimization with Continuous Normalizing Flow in Reinforcement Learning
by: Yang, Shunpeng, et al.
Published: (2026)

Communication-Aware Reinforcement Learning for Cooperative Adaptive Cruise Control
by: Jiang, Sicong, et al.
Published: (2024)

FlowPG: Action-constrained Policy Gradient with Normalizing Flows
by: Brahmanage, Janaka Chathuranga, et al.
Published: (2024)

A Gentle Introduction and Tutorial on Deep Generative Models in Transportation Research
by: Choi, Seongjin, et al.
Published: (2024)