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Stochastic Processes

2667 directly classified papers

Papers per year

Papers

Shoreline: Data-Driven Threshold Estimation of Online Reserves of Cryptocurrency Trading Platforms AAAI 2020
Statistical Estimation of the Poincaré constant and Application to Sampling Multimodal Distributions 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
Structured Conditional Continuous Normalizing Flows for Efficient Amortized Inference in Graphical Models AISTATS 2020
Stein Variational Inference for Discrete Distributions AISTATS 2020
Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations AAAI 2020
Deep Time-Stream Framework for Click-through Rate Prediction by Tracking Interest Evolution AAAI 2020
Neural Temporal Opinion Modelling for Opinion Prediction on Twitter ACL 2020
Torch-Struct: Deep Structured Prediction Library ACL 2020
Option Discovery in the Absence of Rewards with Manifold Analysis ICML 2020
Counterfactual Off-Policy Training for Neural Dialogue Generation EMNLP 2020
Fast and Flexible Temporal Point Processes with Triangular Maps NIPS 2020
Gradient Temporal-Difference Learning with Regularized Corrections ICML 2020
A Statistical Framework for Low-bitwidth Training of Deep Neural Networks NIPS 2020
Bayesian Deep Ensembles via the Neural Tangent Kernel NIPS 2020
Bootstrapping neural processes NIPS 2020
Bandit Samplers for Training Graph Neural Networks NIPS 2020
Towards Theoretically Understanding Why Sgd Generalizes Better Than Adam in Deep Learning NIPS 2020
Approximate Inference with Wasserstein Gradient Flows AISTATS 2020
Distributed, partially collapsed MCMC for Bayesian Nonparametrics AISTATS 2020
A Theoretical Case Study of Structured Variational Inference for Community Detection AISTATS 2020
Scalable Gradients for Stochastic Differential Equations AISTATS 2020
Walsh-Hadamard Variational Inference for Bayesian Deep Learning NIPS 2020
Improved Techniques for Training Score-Based Generative Models NIPS 2020