Image de couverture de livre

Social Processes: Probabilistic Meta-learning for Adaptive Multiparty Interaction Forecasting

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Jučas, Augustinas, Raman, Chirag
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Learning Nonverbal Cues in Multiparty Social Interactions for Robotic Facilitators
par: Martin-Ozimek, Antonio Lech, et autres
Publié: (2025)

External Data-Enhanced Meta-Representation for Adaptive Probabilistic Load Forecasting
par: Li, Haoran, et autres
Publié: (2025)

Probabilistic Forecasting with Stochastic Interpolants and Föllmer Processes
par: Chen, Yifan, et autres
Publié: (2024)

Probabilistic Load Forecasting Based on Adaptive Online Learning
par: Álvarez, Verónica, et autres
Publié: (2020)

Adaptive Multi-task Learning for Probabilistic Load Forecasting
par: Zaballa, Onintze, et autres
Publié: (2025)

Effective Probabilistic Time Series Forecasting with Fourier Adaptive Noise-Separated Diffusion
par: Wang, Xinyan, et autres
Publié: (2025)

Interacting Diffusion Processes for Event Sequence Forecasting
par: Zeng, Mai, et autres
Publié: (2023)

Meta-learning and Data Augmentation for Stress Testing Forecasting Models
par: Inácio, Ricardo, et autres
Publié: (2024)

SSM-CGM: Interpretable State-Space Forecasting Model of Continuous Glucose Monitoring for Personalized Diabetes Management
par: Isaac, Shakson, et autres
Publié: (2025)

Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting
par: Kollovieh, Marcel, et autres
Publié: (2024)

Controlled Face Manipulation and Synthesis for Data Augmentation
par: Kirchner, Joris, et autres
Publié: (2026)

MADA: Meta-Adaptive Optimizers through hyper-gradient Descent
par: Ozkara, Kaan, et autres
Publié: (2024)

Calibrated Probabilistic Forecasts for Arbitrary Sequences
par: Marx, Charles, et autres
Publié: (2024)

Probabilistic Traffic Forecasting with Dynamic Regression
par: Zheng, Vincent Zhihao, et autres
Publié: (2023)

UAMDP: Uncertainty-Aware Markov Decision Process for Risk-Constrained Reinforcement Learning from Probabilistic Forecasts
par: Koren, Michal, et autres
Publié: (2025)

Learning Quantum Processes with Quantum Statistical Queries
par: Wadhwa, Chirag, et autres
Publié: (2023)

Generation through the lens of learning theory
par: Li, Jiaxun, et autres
Publié: (2024)

Probabilistic Forecasting via Autoregressive Flow Matching
par: ElGazzar, Ahmed, et autres
Publié: (2025)

Probabilistic Demand Forecasting with Graph Neural Networks
par: Kozodoi, Nikita, et autres
Publié: (2024)

Koopman Ensembles for Probabilistic Time Series Forecasting
par: Frion, Anthony, et autres
Publié: (2024)

Simplifying Random Forests' Probabilistic Forecasts
par: Koster, Nils, et autres
Publié: (2024)

Training Differentially Private Models with Secure Multiparty Computation
par: Pentyala, Sikha, et autres
Publié: (2022)

The Optimal Sample Complexity of Multiclass and List Learning
par: Pabbaraju, Chirag
Publié: (2026)

A Comparative Study of Garment Draping Techniques
par: Achar, Prerana, et autres
Publié: (2024)

Multi-task Online Learning for Probabilistic Load Forecasting
par: Zaballa, Onintze, et autres
Publié: (2025)

Agnostic Process Tomography
par: Wadhwa, Chirag, et autres
Publié: (2024)

Probabilistic Circuits for Irregular Multivariate Time Series Forecasting
par: Klötergens, Christian, et autres
Publié: (2026)

Probabilistic Multivariate Time Series Forecasting with Diffusion Copulas
par: Huk, David, et autres
Publié: (2026)

Deep and Probabilistic Solar Irradiance Forecast at the Arctic Circle
par: Erdmann, Niklas, et autres
Publié: (2024)

Bayesian Transformer for Probabilistic Load Forecasting in Smart Grids
par: Debnath, Sajib, et autres
Publié: (2026)

Better Batch for Deep Probabilistic Time Series Forecasting
par: Zheng, Vincent Zhihao, et autres
Publié: (2023)

Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks
par: Oskarsson, Joel, et autres
Publié: (2024)

Hyperparameter Tuning MLPs for Probabilistic Time Series Forecasting
par: Madhusudhanan, Kiran, et autres
Publié: (2024)

Multivariate Probabilistic Time Series Forecasting with Correlated Errors
par: Zheng, Vincent Zhihao, et autres
Publié: (2024)

Probabilistic Forecasting of Radiation Exposure for Spaceflight
par: Gurav, Rutuja, et autres
Publié: (2024)

Generation from Noisy Examples
par: Raman, Ananth, et autres
Publié: (2025)

Gaussian Process Assisted Meta-learning for Image Classification and Object Detection Models
par: Flowers, Anna R., et autres
Publié: (2025)

ASTGI: Adaptive Spatio-Temporal Graph Interactions for Irregular Multivariate Time Series Forecasting
par: Liu, Xvyuan, et autres
Publié: (2025)

TimeGMM: Single-Pass Probabilistic Forecasting via Adaptive Gaussian Mixture Models with Reversible Normalization
par: Liu, Lei, et autres
Publié: (2026)

ATLAS: Adapting Trajectory Lengths and Step-Size for Hamiltonian Monte Carlo
par: Modi, Chirag
Publié: (2024)