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Decision Making

203 papers with code · Reasoning

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Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling

ICLR 2018 tensorflow/models

At the same time, advances in approximate Bayesian methods have made posterior approximation for flexible neural network models practical.

DECISION MAKING MULTI-ARMED BANDITS

Relational inductive biases, deep learning, and graph networks

4 Jun 2018deepmind/graph_nets

As a companion to this paper, we have released an open-source software library for building graph networks, with demonstrations of how to use them in practice.

DECISION MAKING RELATIONAL REASONING

QUOTA: The Quantile Option Architecture for Reinforcement Learning

5 Nov 2018ShangtongZhang/DeepRL

In this paper, we propose the Quantile Option Architecture (QUOTA) for exploration based on recent advances in distributional reinforcement learning (RL).

DECISION MAKING DISTRIBUTIONAL REINFORCEMENT LEARNING

Soft Actor-Critic Algorithms and Applications

13 Dec 2018hill-a/stable-baselines

A fork of OpenAI Baselines, implementations of reinforcement learning algorithms

DECISION MAKING

Hierarchical Text Generation and Planning for Strategic Dialogue

ICML 2018 facebookresearch/end-to-end-negotiator

End-to-end models for goal-orientated dialogue are challenging to train, because linguistic and strategic aspects are entangled in latent state vectors.

DECISION MAKING TEXT GENERATION

Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding

9 Nov 2015alexgkendall/caffe-segnet

Semantic segmentation is an important tool for visual scene understanding and a meaningful measure of uncertainty is essential for decision making.

DECISION MAKING SCENE UNDERSTANDING SEMANTIC SEGMENTATION

AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias

3 Oct 2018IBM/AIF360

Such architectural design and abstractions enable researchers and developers to extend the toolkit with their new algorithms and improvements, and to use it for performance benchmarking.

DECISION MAKING

The Consciousness Prior

25 Sep 2017off99555/machine-learning-curriculum

To the extent that these assumptions are generally true (and the form of natural language seems consistent with them), they can form a useful prior for representation learning.

DECISION MAKING REPRESENTATION LEARNING

Deep Reinforcement Learning For Sequence to Sequence Models

24 May 2018yaserkl/RLSeq2Seq

In this survey, we consider seq2seq problems from the RL point of view and provide a formulation combining the power of RL methods in decision-making with sequence-to-sequence models that enable remembering long-term memories.

ABSTRACTIVE TEXT SUMMARIZATION DECISION MAKING MACHINE TRANSLATION