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02/18/2023
Approximate Thompson Sampling via Epistemic Neural Networks
Thompson sampling (TS) is a popular heuristic for action selection, but ...
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11/03/2022
Fine-Tuning Language Models via Epistemic Neural Networks
Large language models are now part of a powerful new paradigm in machine...
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07/01/2022
Robustness of Epinets against Distributional Shifts
Recent work introduced the epinet as a new approach to uncertainty model...
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06/08/2022
Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping
In machine learning, an agent needs to estimate uncertainty to efficient...
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02/28/2022
Evaluating High-Order Predictive Distributions in Deep Learning
Most work on supervised learning research has focused on marginal predic...
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10/09/2021
Evaluating Predictive Distributions: Does Bayesian Deep Learning Work?
Posterior predictive distributions quantify uncertainties ignored by poi...
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07/20/2021
Evaluating Probabilistic Inference in Deep Learning: Beyond Marginal Predictions
A fundamental challenge for any intelligent system is prediction: given ...
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07/19/2021
Epistemic Neural Networks
We introduce the epistemic neural network (ENN) as an interface for unce...
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03/06/2021
Reinforcement Learning, Bit by Bit
Reinforcement learning agents have demonstrated remarkable achievements ...
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06/12/2020
Hypermodels for Exploration
We study the use of hypermodels to represent epistemic uncertainty and g...
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06/09/2020
Stochastic matrix games with bandit feedback
We study a version of the classical zero-sum matrix game with unknown pa...
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01/03/2020
Making Sense of Reinforcement Learning and Probabilistic Inference
Reinforcement learning (RL) combines a control problem with statistical ...
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08/09/2019
Behaviour Suite for Reinforcement Learning
This paper introduces the Behaviour Suite for Reinforcement Learning, or...
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05/08/2019
Meta-learning of Sequential Strategies
In this report we review memory-based meta-learning as a tool for buildi...
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06/08/2018
Randomized Prior Functions for Deep Reinforcement Learning
Dealing with uncertainty is essential for efficient reinforcement learni...
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05/23/2018
Scalable Coordinated Exploration in Concurrent Reinforcement Learning
We consider a team of reinforcement learning agents that concurrently op...
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09/15/2017
The Uncertainty Bellman Equation and Exploration
We consider the exploration/exploitation problem in reinforcement learni...
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06/30/2017
Noisy Networks for Exploration
We introduce NoisyNet, a deep reinforcement learning agent with parametr...
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06/13/2017
On Optimistic versus Randomized Exploration in Reinforcement Learning
We discuss the relative merits of optimistic and randomized approaches t...
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04/12/2017
Deep Q-learning from Demonstrations
Deep reinforcement learning (RL) has achieved several high profile succe...
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03/22/2017
Deep Exploration via Randomized Value Functions
We study the use of randomized value functions to guide deep exploration...
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03/16/2017
Minimax Regret Bounds for Reinforcement Learning
We consider the problem of provably optimal exploration in reinforcement...
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02/14/2017
Gaussian-Dirichlet Posterior Dominance in Sequential Learning
We consider the problem of sequential learning from categorical observat...
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08/09/2016
On Lower Bounds for Regret in Reinforcement Learning
This is a brief technical note to clarify the state of lower bounds on r...
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08/09/2016
Posterior Sampling for Reinforcement Learning Without Episodes
This is a brief technical note to clarify some of the issues with applyi...
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07/01/2016
Why is Posterior Sampling Better than Optimism for Reinforcement Learning?
Computational results demonstrate that posterior sampling for reinforcem...
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02/15/2016
Deep Exploration via Bootstrapped DQN
Efficient exploration in complex environments remains a major challenge ...
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07/01/2015
Bootstrapped Thompson Sampling and Deep Exploration
This technical note presents a new approach to carrying out the kind of ...
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03/15/2014
Near-optimal Reinforcement Learning in Factored MDPs
Any reinforcement learning algorithm that applies to all Markov decision...
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02/04/2014
Generalization and Exploration via Randomized Value Functions
We propose randomized least-squares value iteration (RLSVI) -- a new rei...
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06/04/2013