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Probability

519 papers (95 classified directly here)

Subtopics

Stochastic Processes (438)

Papers per year

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Papers (including subtopics)

Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data IJCAI 2020
ASR-Free Pronunciation Assessment INTERSPEECH 2020
Memoryless Sequences for General Losses JMLR 2020
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients JMLR 2020
Asymptotic Analysis via Stochastic Differential Equations of Gradient Descent Algorithms in Statistical and Computational Paradigms JMLR 2020
Risk Bounds for Reservoir Computing JMLR 2020
Stable Reinforcement Learning with Unbounded State Space L4DC 2020
Constraing-Based Learning for Continous-Time Bayesian Networks PGM 2020
On the Relationship Between Probabilistic Circuits and Determinantal Point Processes UAI 2020
State Aggregation Learning from Markov Transition Data NIPS 2019
Concentration of risk measures: A Wasserstein distance approach NIPS 2019
On two ways to use determinantal point processes for Monte Carlo integration NIPS 2019
Online Markov Decoding: Lower Bounds and Near-Optimal Approximation Algorithms NIPS 2019
Neural Jump Stochastic Differential Equations NIPS 2019
McDiarmid-Type Inequalities for Graph-Dependent Variables and Stability Bounds NIPS 2019
Learning Multiple Markov Chains via Adaptive Allocation NIPS 2019
Continuous-time Models for Stochastic Optimization Algorithms NIPS 2019
Sliced Gromov-Wasserstein NIPS 2019
Estimating Convergence of Markov chains with L-Lag Couplings NIPS 2019
Elliptical Perturbations for Differential Privacy NIPS 2019
Learning low-dimensional state embeddings and metastable clusters from time series data NIPS 2019
Band-Limited Gaussian Processes: The Sinc Kernel NIPS 2019
Thinning for Accelerating the Learning of Point Processes NIPS 2019
Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory NIPS 2019
Variational Optimization Based Reinforcement Learning for Infinite Dimensional Stochastic Systems CORL 2019