Cover Image

Streaming Gaussian Dirichlet Random Fields for Spatial Predictions of High Dimensional Categorical Observations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Soucie, J. E. San, Sosik, H. M., Girdhar, Y.
Format:	Preprint
Published:	2024
Subjects:	Robotics Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Demonstration Sidetracks: Categorizing Systematic Non-Optimality in Human Demonstrations
by: Fang, Shijie, et al.
Published: (2025)

GaussianSSC: Triplane-Guided Directional Gaussian Fields for 3D Semantic Completion
by: Xian, Ruiqi, et al.
Published: (2026)

Bayesian Inverse Games with High-Dimensional Multi-Modal Observations
by: Jain, Yash, et al.
Published: (2026)

Prediction of Acoustic Communication Performance for AUVs using Gaussian Process Classification
by: Gao, Yifei, et al.
Published: (2024)

RN-D: Discretized Categorical Actors with Regularized Networks for On-Policy Reinforcement Learning
by: Bian, Yuexin, et al.
Published: (2026)

Safe Bayesian Optimization for the Control of High-Dimensional Embodied Systems
by: Wei, Yunyue, et al.
Published: (2024)

Spatial Temporal Attention based Target Vehicle Trajectory Prediction for Internet of Vehicles
by: Huang, Ouhan, et al.
Published: (2025)

Conformalized Teleoperation: Confidently Mapping Human Inputs to High-Dimensional Robot Actions
by: Zhao, Michelle, et al.
Published: (2024)

Scalable Exploration for High-Dimensional Continuous Control via Value-Guided Flow
by: Wei, Yunyue, et al.
Published: (2026)

Decoding High-Dimensional Finger Motion from EMG Using Riemannian Features and RNNs
by: Colot, Martin, et al.
Published: (2026)

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control
by: Kim, Donghu, et al.
Published: (2026)

[Re] The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Non-Gaussian Observation Models
by: Casco-Rodriguez, Josue, et al.
Published: (2024)

Learning Efficient Flocking Control based on Gibbs Random Fields
by: Zhang, Dengyu, et al.
Published: (2025)

Decentralized Gaussian Process Classification and an Application in Subsea Robotics
by: Gao, Yifei, et al.
Published: (2025)

SCDP: Learning Humanoid Locomotion from Partial Observations via Mixed-Observation Distillation
by: Carroll, Milo, et al.
Published: (2026)

Detecting Domain Shifts in Myoelectric Activations: Challenges and Opportunities in Stream Learning
by: Sun, Yibin, et al.
Published: (2025)

Quasi-Periodic Gaussian Process Predictive Iterative Learning Control
by: Nigam, Unnati, et al.
Published: (2026)

A Distributed Gaussian Process Model for Multi-Robot Mapping
by: Nabarro, Seth, et al.
Published: (2026)

Generation of Uncertainty-Aware High-Level Spatial Concepts in Factorized 3D Scene Graphs via Graph Neural Networks
by: Millan-Romera, Jose Andres, et al.
Published: (2024)

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation
by: Danesh, Mohamad H., et al.
Published: (2025)

A Tutorial on Gaussian Process Learning-based Model Predictive Control
by: Wang, Jie, et al.
Published: (2024)

Run-time Observation Interventions Make Vision-Language-Action Models More Visually Robust
by: Hancock, Asher J., et al.
Published: (2024)

Using High-Level Patterns to Estimate How Humans Predict a Robot will Behave
by: Parekh, Sagar, et al.
Published: (2024)

Gaussian Variational Inference with Non-Gaussian Factors for State Estimation: A UWB Localization Case Study
by: Stirling, Andrew, et al.
Published: (2025)

An Intuitive Tutorial to Gaussian Process Regression
by: Wang, Jie
Published: (2020)

Population-Coded Spiking Neural Networks for High-Dimensional Robotic Control
by: Jaisankar, Kanishkha, et al.
Published: (2025)

Statistical Guarantees for Offline Domain Randomization
by: Fickinger, Arnaud, et al.
Published: (2025)

Domain Randomization via Entropy Maximization
by: Tiboni, Gabriele, et al.
Published: (2023)

Reward Redistribution via Gaussian Process Likelihood Estimation
by: Xiao, Minheng, et al.
Published: (2025)

Observation-Augmented Contextual Multi-Armed Bandits for Robotic Search and Exploration
by: Wakayama, Shohei, et al.
Published: (2023)

Egocentric Tactile and Proximity Sensors as Observation Priors for Humanoid Collision Avoidance
by: Kohlbrenner, Carson, et al.
Published: (2026)

Cost Function Estimation Using Inverse Reinforcement Learning with Minimal Observations
by: Mehrdad, Sarmad, et al.
Published: (2025)

Multi-Embodiment Locomotion at Scale with extreme Embodiment Randomization
by: Bohlinger, Nico, et al.
Published: (2025)

A Unifying Variational Framework for Gaussian Process Motion Planning
by: Cosier, Lucas, et al.
Published: (2023)

Composite Gaussian Processes Flows for Learning Discontinuous Multimodal Policies
by: Wang, Shu-yuan, et al.
Published: (2025)

Learning Emergent Gaits with Decentralized Phase Oscillators: on the role of Observations, Rewards, and Feedback
by: Zhang, Jenny, et al.
Published: (2024)

Delay-Aware Diffusion Policy: Bridging the Observation-Execution Gap in Dynamic Tasks
by: Liao, Aileen, et al.
Published: (2025)

Improving Generalization Ability of Robotic Imitation Learning by Resolving Causal Confusion in Observations
by: Chen, Yifei, et al.
Published: (2025)

Predictive Planner for Autonomous Driving with Consistency Models
by: Li, Anjian, et al.
Published: (2025)

Estimating the Joint Probability of Scenario Parameters with Gaussian Mixture Copula Models
by: Reichenbächer, Christian, et al.
Published: (2025)