continuous-time

[IEEE T-RO 2025] iKalibr: Multi-Sensor Calibration (Extrinsics & Time Offsets)

A collection of GTSAM factors and optimizers for point cloud SLAM

[RA-L 2024] In Defense of LiDAR-Only Odometry Using an Effective Continuous-Time Trajectory

Closed-form Preintegration for Graph-based Visual-Inertial Navigation

Modular, open-source implementations of continuous-time simultaneous localization and mapping algorithms.

The first 6-DoF spline-based recursive motion esimator for LiDAR-based odometry

Symbolic Continuous-Time Gaussian Belief Propagation Framework with Ceres Interoperability

SFUISE is a novel continuous-time UWB-inertial state estimation framework based on sliding-window spline fusion.

[IEEE RA-L 2024] River: A Tightly-Coupled Radar-Inertial Velocity Estimator Based on Continuous-Time Optimization

Continuous-time multi-agent crowd simulation engine implemented in Python using Numba and Numpy for performance.

PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series".

Official repository of SFUISE, a novel continuous-time UWB-inertial state estimation framework based on sliding-window spline fusion.

Neural Laplace Control for Continuous-time Delayed Systems - an offline RL method combining Neural Laplace dynamics model and MPC planner to achieve near-expert policy performance in environments with irregular time intervals and an unknown constant delay.

Collection of discrete- and continuous-time motion parametrizations.

Simplest simulation to use non-Exponential transitions

Parametric analysis/visualization of model/measurement/simulation results

FluidLM is a Transformer-free language model replacing O(N²) self-attention with reaction-diffusion PDEs - achieving O(N) scaling, adaptive computation, and no KV-cache.

ICML 2026 Spotlight: latent diffusion for irregular multivariate forecasting and imputation.

Author implementation of DSUP(q) algorithms from the NeurIPS 2024 paper "Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning"

A Julia package that provides high-level abstractions for simulating and deploying stochastic filters