Exploring relationships between discrete and continuous time models
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Updated
Sep 13, 2024 - HTML
Exploring relationships between discrete and continuous time models
An Adaptive Tightly-coupled Motion Estimator for Multi-LiDAR, Multi-Camera, and Multi-IMU Systems via Continuous-time Optimization
A Julia package that provides high-level abstractions for simulating and deploying stochastic filters
Alternative (torch) author implementation of algorithms from the NeurIPS 2024 paper "Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning"
End-to-end Python implementation of Huang's (2025) continuous-time RL methodology for asset-liability management. Features model-free soft actor-critic with adaptive exploration, entropy regularization, and Euler-Maruyama SDE simulation. Includes 7 baselines (SAC/PPO/DDPG/CPPI/ACS/MBP), parallelized execution, and Wilcoxon statistical validation.
Ejemplos de diversas fuentes. Examples from various sources. Related to GNU Octave
A continuous depth language model framework in Julia, implementing Neural ODE Transformers, custom continuous attention integrators, reversible depth architectures, adjoint-based training, and efficient KV-cached inference.
A Continuous-time Markov Chain is a type of Markov Chain where the time between transitions is modeled by a probability distribution, rather than being fixed.
Research compendium for the manuscript Pesigan, I. J. A., Russell, M. A., & Chow, S.-M. (2025). Inferences and Effect Sizes for Direct, Indirect, and Total Effects in Continuous-Time Mediation Models. Psychological Methods.
Parametric analysis/visualization of model/measurement/simulation results
cTMed: Continuous-Time Mediation (Pesigan, Russell, & Chow, 2025: https://doi.org/10.1037/met0000779).
Author implementation of DSUP(q) algorithms from the NeurIPS 2024 paper "Action Gaps and Advantages in Continuous-Time Distributional Reinforcement Learning"
🤖 Leverage continuous-time reinforcement learning to optimize asset-liability management and enhance financial decision-making.
Simplest simulation to use non-Exponential transitions
Code for the paper Multilevel Particle Filters for the Non-Linear Filtering Problem in Continuous Time
A framework for hierarchical modelling, simulation and analysis of dynamic systems
Official repository of SFUISE, a novel continuous-time UWB-inertial state estimation framework based on sliding-window spline fusion.
Collection of discrete- and continuous-time motion parametrizations.
PyTorch implementation of the NCDSSM models presented in the ICML '23 paper "Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series".
continuout-time-based state representation and optimization library
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