Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model
Fuente:
arXiv
Saved in:
| Main Authors: | Zanger, Moritz A., Van der Vaart, Pascal R., Böhmer, Wendelin, Spaan, Matthijs T. J. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
On the Equivalence of Random Network Distillation, Deep Ensembles, and Bayesian Inference
by: Zanger, Moritz A., et al.
Published: (2026)
by: Zanger, Moritz A., et al.
Published: (2026)
Diverse Projection Ensembles for Distributional Reinforcement Learning
by: Zanger, Moritz A., et al.
Published: (2023)
by: Zanger, Moritz A., et al.
Published: (2023)
How Ensembles of Distilled Policies Improve Generalisation in Reinforcement Learning
by: Weltevrede, Max, et al.
Published: (2025)
by: Weltevrede, Max, et al.
Published: (2025)
Universal Value-Function Uncertainties
by: Zanger, Moritz A., et al.
Published: (2025)
by: Zanger, Moritz A., et al.
Published: (2025)
Value Improved Actor Critic Algorithms
by: Oren, Yaniv, et al.
Published: (2024)
by: Oren, Yaniv, et al.
Published: (2024)
Exploration Implies Data Augmentation: Reachability and Generalisation in Contextual MDPs
by: Weltevrede, Max, et al.
Published: (2024)
by: Weltevrede, Max, et al.
Published: (2024)
Twice Sequential Monte Carlo for Tree Search
by: Oren, Yaniv, et al.
Published: (2025)
by: Oren, Yaniv, et al.
Published: (2025)
Epistemic Monte Carlo Tree Search
by: Oren, Yaniv, et al.
Published: (2022)
by: Oren, Yaniv, et al.
Published: (2022)
Explore-Go: Leveraging Exploration for Generalisation in Deep Reinforcement Learning
by: Weltevrede, Max, et al.
Published: (2024)
by: Weltevrede, Max, et al.
Published: (2024)
Priors Matter: Addressing Misspecification in Bayesian Deep Q-Learning
by: van der Vaart, Pascal R., et al.
Published: (2025)
by: van der Vaart, Pascal R., et al.
Published: (2025)
Improving Robustness of AlphaZero Algorithms to Test-Time Environment Changes
by: Tamassia, Isidoro, et al.
Published: (2025)
by: Tamassia, Isidoro, et al.
Published: (2025)
TransZero: Parallel Tree Expansion in MuZero using Transformer Networks
by: Malmsten, Emil, et al.
Published: (2025)
by: Malmsten, Emil, et al.
Published: (2025)
Sparse Masked Attention Policies for Reliable Generalization
by: Horsch, Caroline, et al.
Published: (2026)
by: Horsch, Caroline, et al.
Published: (2026)
Positive Experience Reflection for Agents in Interactive Text Environments
by: Lippmann, Philip, et al.
Published: (2024)
by: Lippmann, Philip, et al.
Published: (2024)
Generalisation to unseen topologies: Towards control of biological neural network activity
by: Engwegen, Laurens, et al.
Published: (2024)
by: Engwegen, Laurens, et al.
Published: (2024)
Credal Ensemble Distillation for Uncertainty Quantification
by: Wang, Kaizheng, et al.
Published: (2025)
by: Wang, Kaizheng, et al.
Published: (2025)
EfficientTDMPC: Improved MPC Objectives for Sample-Efficient Continuous Control
by: Evers, Thomas, et al.
Published: (2026)
by: Evers, Thomas, et al.
Published: (2026)
PMCTS: Particle Monte Carlo Tree Search for Principled Parallelized Inference Time Scaling
by: Oren, Yaniv, et al.
Published: (2026)
by: Oren, Yaniv, et al.
Published: (2026)
Modular Recurrence in Contextual MDPs for Universal Morphology Control
by: Engwegen, Laurens, et al.
Published: (2025)
by: Engwegen, Laurens, et al.
Published: (2025)
Reinforcement Learning by Guided Safe Exploration
by: Yang, Qisong, et al.
Published: (2023)
by: Yang, Qisong, et al.
Published: (2023)
HybridFlow: Quantification of Aleatoric and Epistemic Uncertainty with a Single Hybrid Model
by: Van Katwyk, Peter, et al.
Published: (2025)
by: Van Katwyk, Peter, et al.
Published: (2025)
Tree Ensembles for Contextual Bandits
by: Nilsson, Hannes, et al.
Published: (2024)
by: Nilsson, Hannes, et al.
Published: (2024)
RecBayes: Recurrent Bayesian Ad Hoc Teamwork in Large Partially Observable Domains
by: Ribeiro, João G., et al.
Published: (2025)
by: Ribeiro, João G., et al.
Published: (2025)
Pessimistic Iterative Planning with RNNs for Robust POMDPs
by: Galesloot, Maris F. L., et al.
Published: (2024)
by: Galesloot, Maris F. L., et al.
Published: (2024)
Dealing with Uncertainty in Contextual Anomaly Detection
by: Bindini, Luca, et al.
Published: (2025)
by: Bindini, Luca, et al.
Published: (2025)
Provable Anytime Ensemble Sampling Algorithms in Nonlinear Contextual Bandits
by: Sun, Jiazheng, et al.
Published: (2025)
by: Sun, Jiazheng, et al.
Published: (2025)
Minimax Rates and Spectral Distillation for Tree Ensembles
by: Vu, Binh Duc, et al.
Published: (2026)
by: Vu, Binh Duc, et al.
Published: (2026)
VariBASed: Variational Bayes-Adaptive Sequential Monte-Carlo Planning for Deep Reinforcement Learning
by: de Vries, Joery A., et al.
Published: (2026)
by: de Vries, Joery A., et al.
Published: (2026)
DUET: Distilled LLM Unlearning from an Efficiently Contextualized Teacher
by: Zhong, Yisheng, et al.
Published: (2026)
by: Zhong, Yisheng, et al.
Published: (2026)
Similarity and Dissimilarity Guided Co-association Matrix Construction for Ensemble Clustering
by: Zhang, Xu, et al.
Published: (2024)
by: Zhang, Xu, et al.
Published: (2024)
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning
by: Deuschel, Jannik, et al.
Published: (2023)
by: Deuschel, Jannik, et al.
Published: (2023)
Preserving Node Distinctness in Graph Autoencoders via Similarity Distillation
by: Chen, Ge, et al.
Published: (2024)
by: Chen, Ge, et al.
Published: (2024)
Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass
by: Chen, Tong, et al.
Published: (2024)
by: Chen, Tong, et al.
Published: (2024)
GNN's Uncertainty Quantification using Self-Distillation
by: Daneshvar, Hirad, et al.
Published: (2025)
by: Daneshvar, Hirad, et al.
Published: (2025)
Efficient Epistemic Uncertainty Estimation in Regression Ensemble Models Using Pairwise-Distance Estimators
by: Berry, Lucas, et al.
Published: (2023)
by: Berry, Lucas, et al.
Published: (2023)
Efficient Epistemic Uncertainty Estimation for Large Language Models via Knowledge Distillation
by: Park, Seonghyeon, et al.
Published: (2026)
by: Park, Seonghyeon, et al.
Published: (2026)
GP-MoLFormer-Sim: Test Time Molecular Optimization through Contextual Similarity Guidance
by: Navratil, Jiri, et al.
Published: (2025)
by: Navratil, Jiri, et al.
Published: (2025)
Ensemble Distillation for Unsupervised Constituency Parsing
by: Shayegh, Behzad, et al.
Published: (2023)
by: Shayegh, Behzad, et al.
Published: (2023)
Beyond Feature Fusion: Contextual Bayesian PEFT for Multimodal Uncertainty Estimation
by: Naderi, Habibeh, et al.
Published: (2026)
by: Naderi, Habibeh, et al.
Published: (2026)
Logical Distillation of Graph Neural Networks
by: Pluska, Alexander, et al.
Published: (2024)
by: Pluska, Alexander, et al.
Published: (2024)
Similar Items
-
On the Equivalence of Random Network Distillation, Deep Ensembles, and Bayesian Inference
by: Zanger, Moritz A., et al.
Published: (2026) -
Diverse Projection Ensembles for Distributional Reinforcement Learning
by: Zanger, Moritz A., et al.
Published: (2023) -
How Ensembles of Distilled Policies Improve Generalisation in Reinforcement Learning
by: Weltevrede, Max, et al.
Published: (2025) -
Universal Value-Function Uncertainties
by: Zanger, Moritz A., et al.
Published: (2025) -
Value Improved Actor Critic Algorithms
by: Oren, Yaniv, et al.
Published: (2024)