
Acquisition of Chess Knowledge in AlphaZero
What is learned by sophisticated neural network agents such as AlphaZero...
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Assessing Game Balance with AlphaZero: Exploring Alternative Rule Sets in Chess
It is nontrivial to design engaging and balanced sets of game rules. Mo...
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Unsupervised Separation of Dynamics from Pixels
We present an approach to learn the dynamics of multiple objects from im...
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A Factorial Mixture Prior for Compositional Deep Generative Models
We assume that a highdimensional datum, like an image, is a composition...
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An Efficient Implementation of Riemannian Manifold Hamiltonian Monte Carlo for Gaussian Process Models
This technical report presents pseudocode for a Riemannian manifold Ham...
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Recurrent Relational Networks for Complex Relational Reasoning
Humans possess an ability to abstractly reason about objects and their i...
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A Disentangled Recognition and Nonlinear Dynamics Model for Unsupervised Learning
This paper takes a step towards temporal reasoning in a dynamically chan...
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The Bayesian LowRank Determinantal Point Process Mixture Model
Determinantal point processes (DPPs) are an elegant model for encoding p...
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Sequential Neural Models with Stochastic Layers
How can we efficiently propagate uncertainty in a latent state represent...
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An Adaptive ResampleMove Algorithm for Estimating Normalizing Constants
The estimation of normalizing constants is a fundamental step in probabi...
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LowRank Factorization of Determinantal Point Processes for Recommendation
Determinantal point processes (DPPs) have garnered attention as an elega...
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Oneclass Collaborative Filtering with Random Graphs: Annotated Version
The bane of oneclass collaborative filtering is interpreting and modell...
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Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models
Expectation Propagation (EP) provides a framework for approximate infere...
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Ulrich Paquet
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