Partial Observation

Partial observation, the challenge of inferring complete information from incomplete data, is a central problem across numerous scientific disciplines. Current research focuses on developing robust methods for estimating missing information and making accurate predictions despite data limitations, employing techniques like Bayesian optimization, diffusion models, and various neural network architectures (including recurrent GNNs, transformers, and autoencoders) tailored to specific data types and problem structures. These advancements have significant implications for diverse fields, improving the accuracy and efficiency of tasks ranging from epidemiological modeling and quantum state control to robotic navigation and fairness monitoring in AI systems. The ultimate goal is to create reliable and efficient algorithms that can handle incomplete data effectively, unlocking insights from datasets previously considered unusable.

Papers

October 31, 2024

Learning Macroscopic Dynamics from Partial Microscopic Observations
Mengyi Chen, Qianxiao Li
Partial Observation Atomic Knowledge Thermodynamic Observables Closure Model Macroscopic Model

August 21, 2024

Transfer Learning and the Early Estimation of Single-Photon Source Quality using Machine Learning Methods
David Jacob Kedziora, Anna Musiał, Wojciech Rudno-Rudziński, Bogdan Gabrys
Machine Learning Transfer Learning Estimation Task Partial Observation Quantum Technology Single Photon

July 18, 2024

Predictive Low Rank Matrix Learning under Partial Observations: Mixed-Projection ADMM
Dimitris Bertsimas, Nicholas A. G. Johnson
Matrix Completion Partial Observation ADMM Algorithm

July 17, 2024

Estimate Epidemiological Parameters given Partial Observations based on Algebraically Observable PINNs
Mizuka Komatsu
Physic Informed Neural Network Epidemic Forecasting Full Observability Partial Observation Epidemic Model

June 25, 2024

DiffusionPDE: Generative PDE-Solving Under Partial Observation
Jiahe Huang, Guandao Yang, Zichen Wang, Jeong Joon Park
Generative Diffusion Model Partial Observation Generative Prior Inverse PDE Problem

June 12, 2024

Reinforcement Learning to Disentangle Multiqubit Quantum States from Partial Observations
Pavel Tashev, Stefan Petrov, Friederike Metz, Marin Bukov
Reinforcement Learning Quantum State Partial Observation Density Matrix

April 22, 2024

Human Orientation Estimation under Partial Observation
Jieting Zhao, Hanjing Ye, Yu Zhan, Hao Luan, Hong Zhang
Robot Person Orientation Estimation Partial Observation

March 26, 2024

Predicting Species Occurrence Patterns from Partial Observations
Hager Radi Abdelwahed, Mélisande Teng, David Rolnick
Observational Data Partial Observation Specie Complex

March 18, 2024

SceneSense: Diffusion Models for 3D Occupancy Synthesis from Partial Observation
Alec Reed, Brendan Crowe, Doncey Albin, Lorin Achey, Bradley Hayes, Christoffer Heckman
Diffusion Model Occupancy Prediction 3D Occupancy Partial Observation Occupancy Map

February 27, 2024

When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback
Leon Lang, Davis Foote, Stuart Russell, Anca Dragan, Erik Jenner, Scott Emmons
Reinforcement Learning Technical Challenge Human Feedback Partial Observability Partial Observation

February 20, 2024

exploreCOSMOS: Interactive Exploration of Conditional Statistical Shape Models in the Web-Browser
Maximilian Hahn, Bernhard Egger
Computer Vision Medical Image Analysis Posterior Inference Statistical Shape Partial Observation Guided Exploration Web Browser

January 17, 2024

Space and Time Continuous Physics Simulation From Partial Observations
Janny Steeven, Nadri Madiha, Digne Julie, Wolf Christian
Deep Space Fluid Dynamic Physical Simulation Differentiable Physic Partial Observation Large Scale Machine Learning Numerical Scheme Continuous Prediction

December 20, 2023

Gappy local conformal auto-encoders for heterogeneous data fusion: in praise of rigidity
Erez Peterfreund, Iryna Burak, Ofir Lindenbaum, Jim Gimlett, Felix Dietrich, Ronald R. Coifman, Ioannis G. Kevrekidis
Human Feedback Neural Network Architecture Partial Observation Data Fusion Third Order Rigidity

December 6, 2023

Constrained Bayesian Optimization Under Partial Observations: Balanced Improvements and Provable Convergence
Shengbo Wang, Ke Li
Optimization Purpose Bayesian Optimization Surrogate Model Constrained Optimization Partial Observation Data Driven Optimization Provable Convergence

October 30, 2023

Posterior Sampling for Competitive RL: Function Approximation and Partial Observation
Shuang Qiu, Ziyu Dai, Han Zhong, Zhaoran Wang, Zhuoran Yang, Tong Zhang
Posterior Sampling Markov Game Function Approximation Self Play Partial Observation Adversarial Policy

August 1, 2023

Monitoring Algorithmic Fairness under Partial Observations
Thomas A. Henzinger, Konstantin Kueffner, Kaushik Mallik
Algorithmic Fairness Markov Chain Partial Observation Runtime Verification Firth Bias Reduction

July 28, 2023

Equivariance and partial observations in Koopman operator theory for partial differential equations
Sebastian Peitz, Hans Harder, Feliks Nüske, Friedrich Philipp, Manuel Schaller, Karl Worthmann
Large Scale Nonlinear Dynamic Inter Part Equivariance Koopman Operator Partial Observation Coarse Graining dlADMM Algorithm

July 16, 2023

Pseudo-rigid body networks: learning interpretable deformable object dynamics from partial observations
Shamil Mamedov, A. René Geist, Jan Swevers, Sebastian Trimpe
Deformable Object Physic Informed Deformable Linear Object Partial Observation Forward Kinematics

May 30, 2023

Delayed Bandits: When Do Intermediate Observations Help?
Emmanuel Esposito, Saeed Masoudian, Hao Qiu, Dirk van der Hoeven, Nicolò Cesa-Bianchi, Yevgeny Seldin
Stochastic Way Regret Analysis Partial Observation Armed Bandit Regret Rate Delayed Bandit Finite State

April 26, 2023

Regression with Sensor Data Containing Incomplete Observations
Takayuki Katsuki, Takayuki Osogami
Novel Regression Sensor Data Learning Algorithm Partial Observation Regression Problem Combining Machine Learning

Partial Observation

Papers

Learning Macroscopic Dynamics from Partial Microscopic Observations

Transfer Learning and the Early Estimation of Single-Photon Source Quality using Machine Learning Methods

Predictive Low Rank Matrix Learning under Partial Observations: Mixed-Projection ADMM

Estimate Epidemiological Parameters given Partial Observations based on Algebraically Observable PINNs

DiffusionPDE: Generative PDE-Solving Under Partial Observation

Reinforcement Learning to Disentangle Multiqubit Quantum States from Partial Observations

Human Orientation Estimation under Partial Observation

Predicting Species Occurrence Patterns from Partial Observations

SceneSense: Diffusion Models for 3D Occupancy Synthesis from Partial Observation

When Your AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback

exploreCOSMOS: Interactive Exploration of Conditional Statistical Shape Models in the Web-Browser

Space and Time Continuous Physics Simulation From Partial Observations

Gappy local conformal auto-encoders for heterogeneous data fusion: in praise of rigidity

Constrained Bayesian Optimization Under Partial Observations: Balanced Improvements and Provable Convergence

Posterior Sampling for Competitive RL: Function Approximation and Partial Observation

Monitoring Algorithmic Fairness under Partial Observations

Equivariance and partial observations in Koopman operator theory for partial differential equations

Pseudo-rigid body networks: learning interpretable deformable object dynamics from partial observations

Delayed Bandits: When Do Intermediate Observations Help?

Regression with Sensor Data Containing Incomplete Observations