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Probabilistic Modeling

2,599 papers

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Papers

Function-Space Distributions over Kernels NIPS 2019
On Fenchel Mini-Max Learning NIPS 2019
Parameter elimination in particle Gibbs sampling NIPS 2019
Learning Reward Machines for Partially Observable Reinforcement Learning NIPS 2019
Mutually Regressive Point Processes NIPS 2019
Fast Convergence of Belief Propagation to Global Optima: Beyond Correlation Decay NIPS 2019
Scalable Bayesian dynamic covariance modeling with variational Wishart and inverse Wishart processes NIPS 2019
Wide Feedforward or Recurrent Neural Networks of Any Architecture are Gaussian Processes NIPS 2019
No-Regret Learning in Unknown Games with Correlated Payoffs NIPS 2019
Structured Variational Inference in Continuous Cox Process Models NIPS 2019
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model NIPS 2019
Kernel quadrature with DPPs NIPS 2019
Single-Model Uncertainties for Deep Learning NIPS 2019
Multivariate Sparse Coding of Nonstationary Covariances with Gaussian Processes NIPS 2019
Uncertainty on Asynchronous Time Event Prediction NIPS 2019
Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond NIPS 2019
Multiple Futures Prediction NIPS 2019
Learning Hawkes Processes from a handful of events NIPS 2019
Markov Random Fields for Collaborative Filtering NIPS 2019
Smoothing Structured Decomposable Circuits NIPS 2019
Recovering Bandits NIPS 2019
A neurally plausible model for online recognition and postdiction in a dynamical environment NIPS 2019
Scalable Deep Generative Relational Model with High-Order Node Dependence NIPS 2019
Tensor Monte Carlo: Particle Methods for the GPU era NIPS 2019
Combining Generative and Discriminative Models for Hybrid Inference NIPS 2019