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Stochastic Processes

2,667 papers

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Papers

Uncertainty-Aware Curriculum Learning for Neural Machine Translation ACL 2020
Estimating Mutual Information Between Dense Word Embeddings ACL 2020
Torch-Struct: Deep Structured Prediction Library ACL 2020
Collaborative Exploration in Stochastic Multi-Player Bandits ACML 2020
Thompson Sampling for Unsupervised Sequential Selection ACML 2020
Localizing and Amortizing: Efficient Inference for Gaussian Processes ACML 2020
Multiplicative Gaussian Particle Filter AISTATS 2020
Corruption-Tolerant Gaussian Process Bandit Optimization AISTATS 2020
Infinitely deep neural networks as diffusion processes AISTATS 2020
Stable behaviour of infinitely wide deep neural networks AISTATS 2020
Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes AISTATS 2020
Langevin Monte Carlo without smoothness AISTATS 2020
AMAGOLD: Amortized Metropolis Adjustment for Efficient Stochastic Gradient MCMC AISTATS 2020
Dynamic content based ranking AISTATS 2020
Approximate Inference with Wasserstein Gradient Flows AISTATS 2020
Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions AISTATS 2020
Robust Optimisation Monte Carlo AISTATS 2020
Finite-Time Error Bounds for Biased Stochastic Approximation with Applications to Q-Learning AISTATS 2020
Black-Box Inference for Non-Linear Latent Force Models AISTATS 2020
Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes AISTATS 2020
On the interplay between noise and curvature and its effect on optimization and generalization AISTATS 2020
Distributed, partially collapsed MCMC for Bayesian Nonparametrics AISTATS 2020
Prophets, Secretaries, and Maximizing the Probability of Choosing the Best AISTATS 2020
A Theoretical Case Study of Structured Variational Inference for Community Detection AISTATS 2020
Scalable Gradients for Stochastic Differential Equations AISTATS 2020